no code implementations • 23 May 2024 • Supreeth Mysore Venkatesh, Antonio Macaluso, Marlon Nuske, Matthias Klusch, Andreas Dengel
Quantum computing is expected to transform a range of computational tasks beyond the reach of classical algorithms.
no code implementations • 13 May 2024 • Abdul Hannan Khan, Syed Tahseen Raza Rizvi, Dheeraj Varma Chittari Macharavtu, Andreas Dengel
With the aim to avoid collisions and drive safely, autonomous driving systems rely heavily on object detection.
no code implementations • 7 May 2024 • Alireza Koochali, Ensiye Tahaei, Andreas Dengel, Sheraz Ahmed
This paper presents VAEneu, an innovative autoregressive method for multistep ahead univariate probabilistic time series forecasting.
no code implementations • 30 Apr 2024 • Pervaiz Iqbal Khan, Andreas Dengel, Sheraz Ahmed
Detecting diseases from social media has diverse applications, such as public health monitoring and disease spread detection.
no code implementations • 26 Apr 2024 • Brian B. Moser, Ahmed Anwar, Federico Raue, Stanislav Frolov, Andreas Dengel
This distinction is crucial as it circumvents the need to precisely model real-world degradations, which limits contemporary blind image SR research.
no code implementations • 23 Apr 2024 • Dayananda Herurkar, Sebastian Palacio, Ahmed Anwar, Joern Hees, Andreas Dengel
Anomaly detection in real-world scenarios poses challenges due to dynamic and often unknown anomaly distributions, requiring robust methods that operate under an open-world assumption.
no code implementations • 16 Apr 2024 • Payal Varshney, Adriano Lucieri, Christoph Balada, Andreas Dengel, Sheraz Ahmed
In the first step, CDCT uses a Latent Diffusion Model (LDM) to generate a counterfactual trajectory dataset.
no code implementations • 16 Apr 2024 • Mahta Bakhshizadeh, Christian Jilek, Markus Schröder, Heiko Maus, Andreas Dengel
Over the years, various approaches have been employed to enhance the productivity of knowledge workers, from addressing psychological well-being to the development of personal knowledge assistants.
no code implementations • 11 Apr 2024 • Stanislav Frolov, Brian B. Moser, Sebastian Palacio, Andreas Dengel
We present ObjBlur, a novel curriculum learning approach to improve layout-to-image generation models, where the task is to produce realistic images from layouts composed of boxes and labels.
no code implementations • 25 Mar 2024 • Brian B. Moser, Federico Raue, Andreas Dengel
We introduce a novel approach that reduces a dataset to a core-set of training samples, selected based on their loss values as determined by a simple pre-trained SR model.
no code implementations • 25 Mar 2024 • Francisco Mena, Diego Arenas, Andreas Dengel
Deep learning models have proven to be effective for this task by mapping time series data to high-level representation for prediction.
Ranked #1 on Crop Classification on CropHarvest - Brazil
no code implementations • 22 Mar 2024 • Neda Foroutan, Markus Schröder, Andreas Dengel
The process of cyber mapping gives insights in relationships among financial entities and service providers.
1 code implementation • 21 Mar 2024 • Francisco Mena, Diego Arenas, Marcela Charfuelan, Marlon Nuske, Andreas Dengel
In this work, we assess the impact of missing temporal and static EO sources in trained models across four datasets with classification and regression tasks.
no code implementations • 6 Mar 2024 • Brian B. Moser, Federico Raue, Sebastian Palacio, Stanislav Frolov, Andreas Dengel
In response to these limitations, the concept of distilling the information on a dataset into a condensed set of (synthetic) samples, namely a distilled dataset, emerged.
1 code implementation • 5 Mar 2024 • Tobias Christian Nauen, Sebastian Palacio, Andreas Dengel
The quadratic complexity of the attention mechanism represents one of the biggest hurdles for processing long sequences using Transformers.
no code implementations • 21 Feb 2024 • Adrian Höhl, Ivica Obadic, Miguel Ángel Fernández Torres, Hiba Najjar, Dario Oliveira, Zeynep Akata, Andreas Dengel, Xiao Xiang Zhu
In recent years, black-box machine learning approaches have become a dominant modeling paradigm for knowledge extraction in Remote Sensing.
no code implementations • 16 Feb 2024 • Johannes Bayer, Leo van Waveren, Andreas Dengel
However, apart from printed legacy schematics, hand-drawn circuit diagrams are still used today in the educational domain, where they serve as an easily accessible mean for trainees and students to learn drawing this type of diagrams.
no code implementations • 31 Jan 2024 • Abdul Hannan Khan, Syed Tahseen Raza Rizvi, Andreas Dengel
In this research, we assess the robustness of our previously proposed, highly efficient pedestrian detector LSFM on well-established autonomous driving benchmarks, including diverse weather conditions and nighttime scenes.
no code implementations • 22 Jan 2024 • Francisco Mena, Deepak Pathak, Hiba Najjar, Cristhian Sanchez, Patrick Helber, Benjamin Bischke, Peter Habelitz, Miro Miranda, Jayanth Siddamsetty, Marlon Nuske, Marcela Charfuelan, Diego Arenas, Michaela Vollmer, Andreas Dengel
The GU module learned different weights based on the country and crop-type, aligning with the variable significance of each data source to the prediction task.
no code implementations • 1 Jan 2024 • Brian B. Moser, Arundhati S. Shanbhag, Federico Raue, Stanislav Frolov, Sebastian Palacio, Andreas Dengel
Diffusion Models (DMs) have disrupted the image Super-Resolution (SR) field and further closed the gap between image quality and human perceptual preferences.
no code implementations • 20 Dec 2023 • Hamidreza Gholamrezaei, Alireza Koochali, Andreas Dengel, Sheraz Ahmed
This paper introduces Structured Noise Space GAN (SNS-GAN), a novel approach in the field of generative modeling specifically tailored for class-conditional generation in both image and time series data.
1 code implementation • 21 Nov 2023 • Supreeth Mysore Venkatesh, Antonio Macaluso, Marlon Nuske, Matthias Klusch, Andreas Dengel
Thus, Q-Seg emerges as a viable alternative for real-world applications using available quantum hardware, particularly in scenarios where the lack of labeled data and computational runtime are critical.
no code implementations • 31 Oct 2023 • Pervaiz Iqbal Khan, Andreas Dengel, Sheraz Ahmed
This paper proposes a training strategy Medi-CAT to overcome the underfitting and overfitting phenomena in medical imaging datasets.
no code implementations • 29 Oct 2023 • Pervaiz Iqbal Khan, Muhammad Nabeel Asim, Andreas Dengel, Sheraz Ahmed
Following the need for an optimal language model competent in extracting useful patterns from social media text, the key goal of this paper is to train language models in such a way that they learn to derive generalized patterns.
no code implementations • 5 Oct 2023 • Saifullah Saifullah, Stefan Agne, Andreas Dengel, Sheraz Ahmed
We conduct a comprehensive evaluation of the algorithm across various client and privacy settings, and demonstrate its capability to achieve comparable performance and privacy guarantees to standalone DP, even when accommodating an increasing number of participating clients.
1 code implementation • bioRxiv 2023 • Anwai Archit, Sushmita Nair, Nabeel Khalid, Paul Hilt, Vikas Rajashekar, Marei Freitag, Sagnik Gupta, Andreas Dengel, Sheraz Ahmed, Constantin Pape
We present Segment Anything for Microscopy, a tool for interactive and automatic segmentation and tracking of objects in multi-dimensional microscopy data.
1 code implementation • 18 Aug 2023 • Tobias Christian Nauen, Sebastian Palacio, Andreas Dengel
This benchmark provides a standardized baseline across the landscape of efficiency-oriented transformers and our framework of analysis, based on Pareto optimality, reveals surprising insights.
Ranked #265 on Image Classification on ImageNet
no code implementations • 17 Aug 2023 • Deepak Pathak, Miro Miranda, Francisco Mena, Cristhian Sanchez, Patrick Helber, Benjamin Bischke, Peter Habelitz, Hiba Najjar, Jayanth Siddamsetty, Diego Arenas, Michaela Vollmer, Marcela Charfuelan, Marlon Nuske, Andreas Dengel
We introduce a simple yet effective early fusion method for crop yield prediction that handles multiple input modalities with different temporal and spatial resolutions.
no code implementations • 15 Aug 2023 • Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
To address this, we introduce "You Only Diffuse Areas" (YODA), a dynamic attention-guided diffusion method for image SR. YODA selectively focuses on spatial regions using attention maps derived from the low-resolution image and the current time step in the diffusion process.
1 code implementation • 10 Aug 2023 • Francisco Mena, Diego Arenas, Marlon Nuske, Andreas Dengel
Instead, we present a comparison of multi-view fusion methods for three different datasets and show that, depending on the test region, different methods obtain the best performance.
Ranked #2 on Crop Classification on CropHarvest - Togo
no code implementations • 3 Aug 2023 • Christian Jilek, Markus Schröder, Heiko Maus, Sven Schwarz, Andreas Dengel
This paper presents a retrospective overview of a decade of research in our department towards self-organizing personal knowledge assistants in evolving corporate memories.
1 code implementation • 10 Jul 2023 • Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
This work introduces Differential Wavelet Amplifier (DWA), a drop-in module for wavelet-based image Super-Resolution (SR).
1 code implementation • 11 Apr 2023 • Brian Moser, Federico Raue, Jörn Hees, Andreas Dengel
We present new Recurrent Neural Network (RNN) cells for image classification using a Neural Architecture Search (NAS) approach called DARTS.
1 code implementation • 4 Apr 2023 • Brian Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
This paper presents a novel Diffusion-Wavelet (DiWa) approach for Single-Image Super-Resolution (SISR).
no code implementations • 28 Mar 2023 • Dominique Mercier, Andreas Dengel, Sheraz Ahmed
In this work, two very prominent GAN-based architectures were evaluated in the context of private time series classification.
1 code implementation • 1 Mar 2023 • Kevin Iselborn, Marco Stricker, Takashi Miyamoto, Marlon Nuske, Andreas Dengel
Climate change has increased the severity and frequency of weather disasters all around the world.
no code implementations • 31 Jan 2023 • Amin E. Bakhshipour, Alireza Koochali, Ulrich Dittmer, Ali Haghighi, Sheraz Ahmad, Andreas Dengel
In this study, we developed a GAN model to generate synthetic time series to balance our limited recorded time series data and improve the accuracy of a data-driven model for combined sewer flow prediction.
no code implementations • 9 Jan 2023 • Johannes Bayer, Amit Kumar Roy, Andreas Dengel
This paper describes an approach for extracting both the electrical components (including their terminals and describing texts) as well their interconnections (including junctions and wire hops) by the means of instance segmentation and keypoint extraction.
no code implementations • CVPR 2023 • Abdul Hannan Khan, Mohammed Shariq Nawaz, Andreas Dengel
Autonomous driving systems rely heavily on the underlying perception module which needs to be both performant and efficient to allow precise decisions in real-time.
Ranked #1 on Pedestrian Detection on TJU-Ped-traffic
1 code implementation • 20 Dec 2022 • Francisco Mena, Diego Arenas, Marlon Nuske, Andreas Dengel
However, the approaches in the literature vary greatly since different terminology is used to refer to similar concepts or different illustrations are given to similar techniques.
no code implementations • 8 Nov 2022 • Saifullah Saifullah, Dominique Mercier, Adriano Lucieri, Andreas Dengel, Sheraz Ahmed
This work is the first to investigate the impact of private learning techniques on generated explanations for DL-based models.
Explainable Artificial Intelligence (XAI) Privacy Preserving +1
no code implementations • 14 Oct 2022 • Alireza Koochali, Maria Walch, Sankrutyayan Thota, Peter Schichtel, Andreas Dengel, Sheraz Ahmed
Generative models are designed to address the data scarcity problem.
no code implementations • 27 Sep 2022 • Brian Moser, Federico Raue, Stanislav Frolov, Jörn Hees, Sebastian Palacio, Andreas Dengel
With the advent of Deep Learning (DL), Super-Resolution (SR) has also become a thriving research area.
1 code implementation • 13 Jun 2022 • Adriano Lucieri, Fabian Schmeisser, Christoph Peter Balada, Shoaib Ahmed Siddiqui, Andreas Dengel, Sheraz Ahmed
Interestingly, despite deep feature extractors being inclined towards learning entangled features for skin lesion classification, individual features can still be decoded from this entangled representation.
no code implementations • 13 Apr 2022 • Christoph Balada, Sheraz Ahmed, Andreas Dengel, Max Bondorf, Nikolai Hopfer, Markus Zdrallek
To overcome this, power line communication (PLC) has emerged as a potential solution for reliable monitoring of the low-voltage grid.
no code implementations • 13 Apr 2022 • Pervaiz Iqbal Khan, Imran Razzak, Andreas Dengel, Sheraz Ahmed
Moreover, our analysis shows that adding noise at earlier layers improves models' performance whereas adding noise at intermediate layers deteriorates models' performance.
no code implementations • 5 Apr 2022 • Stanislav Frolov, Prateek Bansal, Jörn Hees, Andreas Dengel
Our results demonstrate the capability of our approach to generate plausible images of complex scenes using region captions.
1 code implementation • TechArXiv 2022 • Saifullah, Stefan Agne, Andreas Dengel, Sheraz Ahmed
Our approach achieves a new peak performance in image-based classification on two popular document datasets, namely RVL-CDIP and Tobacco3482, with a top-1 classification accuracy of 94. 17% and 95. 57% on the two datasets, respectively.
Ranked #1 on Document Image Classification on Tobacco-3482
1 code implementation • 14 Mar 2022 • Brian Moser, Federico Raue, Jörn Hees, Andreas Dengel
One of our surprising findings is that in most cases we can reduce the amount of training data to 25\%, consequently reducing search time to 25\%, while at the same time maintaining the same accuracy as if training on the full dataset.
2 code implementations • 4 Mar 2022 • Abdul Hannan Khan, Mohsin Munir, Ludger van Elst, Andreas Dengel
However, the current two-stage detectors are inefficient as they do bounding box regression in multiple steps i. e. in region proposal networks and bounding box heads.
Ranked #2 on Pedestrian Detection on Caltech (using extra training data)
no code implementations • 3 Mar 2022 • Pervaiz Iqbal Khan, Shoaib Ahmed Siddiqui, Imran Razzak, Andreas Dengel, Sheraz Ahmed
The idea is to learn word representation by its surrounding words and utilize emojis in the text to help improve the classification results.
no code implementations • 22 Feb 2022 • Dominique Mercier, Syed Tahseen Raza Rizvi, Vikas Rajashekar, Sheraz Ahmed, Andreas Dengel
However, qualitative aspects provide deeper insights into the impact of a scientific research artifact and make it possible to focus on relevant literature free from bias associated with quantitative aspects.
no code implementations • 16 Feb 2022 • Dominique Mercier, Andreas Dengel, Sheraz Ahmed
Deep neural networks are one of the most successful classifiers across different domains.
no code implementations • 8 Feb 2022 • Dominique Mercier, Jwalin Bhatt, Andreas Dengel, Sheraz Ahmed
However, due to the lack of transparency the use of these networks is hampered in the areas with safety critical areas.
no code implementations • 8 Feb 2022 • Muhammad Ali Chattha, Ludger van Elst, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
End-to-end data-driven machine learning methods often have exuberant requirements in terms of quality and quantity of training data which are often impractical to fulfill in real-world applications.
no code implementations • 21 Jan 2022 • Alireza Koochali, Peter Schichtel, Andreas Dengel, Sheraz Ahmed
The recent developments in the machine learning domain have enabled the development of complex multivariate probabilistic forecasting models.
no code implementations • 4 Jan 2022 • Adriano Lucieri, Muhammad Naseer Bajwa, Stephan Alexander Braun, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
This work presents ExAID (Explainable AI for Dermatology), a novel framework for biomedical image analysis, providing multi-modal concept-based explanations consisting of easy-to-understand textual explanations supplemented by visual maps justifying the predictions.
1 code implementation • 6 Dec 2021 • Shailza Jolly, Zi Xuan Zhang, Andreas Dengel, Lili Mou
To this end, we propose a search-and-learning approach that leverages pretrained language models but inserts the missing slots to improve the semantic coverage.
1 code implementation • 29 Nov 2021 • Dominique Mercier, Adriano Lucieri, Mohsin Munir, Andreas Dengel, Sheraz Ahmed
With the advent of machine learning in applications of critical infrastructure such as healthcare and energy, privacy is a growing concern in the minds of stakeholders.
no code implementations • 18 Sep 2021 • Praveen Tirupattur, Christian Schulze, Andreas Dengel
To address this issue, an approach to automatically detect violent content in videos is proposed in this work.
1 code implementation • Nature Methods 2021 • Christoffer Edlund, Timothy R. Jackson, Nabeel Khalid, Nicola Bevan, Timothy Dale, Andreas Dengel, Sheraz Ahmed, Johan Trygg, Rickard Sjögren
Light microscopy combined with well-established protocols of two-dimensional cell culture facilitates high-throughput quantitative imaging to study biological phenomena.
Ranked #1 on Cell Segmentation on LIVECell
Cell Segmentation Cultural Vocal Bursts Intensity Prediction +4
no code implementations • 22 Aug 2021 • Fatemeh Azimi, Jean-Francois Jacques Nicolas Nies, Sebastian Palacio, Federico Raue, Jörn Hees, Andreas Dengel
Curriculum learning is a bio-inspired training technique that is widely adopted to machine learning for improved optimization and better training of neural networks regarding the convergence rate or obtained accuracy.
no code implementations • IJCNN 2021 • Nabeel Khalid, Mohsin Munir, Christoffer Edlund, Timothy R Jackson, Johan Trygg, Rickard Sjögren, Andreas Dengel, Sheraz Ahmed
To address the aforementioned challenges, DeepCeNS is proposed in this paper to detect and segment cells and nucleus in microscopic images.
Ranked #1 on Cell Segmentation on EVICAN
no code implementations • 27 Jun 2021 • Fatemeh Azimi, Federico Raue, Joern Hees, Andreas Dengel
Spatial Transformer Networks (STN) can generate geometric transformations which modify input images to improve the classifier's performance.
4 code implementations • 24 Jun 2021 • Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
AudioCLIP achieves new state-of-the-art results in the Environmental Sound Classification (ESC) task, out-performing other approaches by reaching accuracies of 90. 07% on the UrbanSound8K and 97. 15% on the ESC-50 datasets.
Ranked #1 on Environmental Sound Classification on ESC-50
no code implementations • 26 May 2021 • Pervaiz Iqbal Khan, Imran Razzak, Andreas Dengel, Sheraz Ahmed
These social media platforms enable users to share information with other users who can reshare this information, thus causing this information to spread.
no code implementations • 21 May 2021 • Ricard Durall, Stanislav Frolov, Jörn Hees, Federico Raue, Franz-Josef Pfreundt, Andreas Dengel, Janis Keupe
Transformer models have recently attracted much interest from computer vision researchers and have since been successfully employed for several problems traditionally addressed with convolutional neural networks.
no code implementations • 14 May 2021 • Sebastian Palacio, Adriano Lucieri, Mohsin Munir, Jörn Hees, Sheraz Ahmed, Andreas Dengel
The field of explainable AI (XAI) has quickly become a thriving and prolific community.
1 code implementation • 25 Mar 2021 • Stanislav Frolov, Avneesh Sharma, Jörn Hees, Tushar Karayil, Federico Raue, Andreas Dengel
In this paper, we propose a method for attribute controlled image synthesis from layout which allows to specify the appearance of individual objects without affecting the rest of the image.
no code implementations • 2 Mar 2021 • Adriano Lucieri, Andreas Dengel, Sheraz Ahmed
Moreover, the possibility to intervene and guide models in case of misbehaviour is identified as a major step towards successful deployment of AI as DL-based DSS and beyond.
no code implementations • 15 Feb 2021 • Shoya Ishimaru, Takanori Maruichi, Andreas Dengel, Koichi Kise
(2) With the help of 20 participants, we observed that correct answer rates of questions were increased by 14% and 17% by giving feedback about correct answers without confidence and incorrect answers with confidence, respectively.
no code implementations • 11 Feb 2021 • Dominique Mercier, Andreas Dengel, Sheraz Ahmed
The classification of time-series data is pivotal for streaming data and comes with many challenges.
no code implementations • 25 Jan 2021 • Stanislav Frolov, Tobias Hinz, Federico Raue, Jörn Hees, Andreas Dengel
With the advent of generative adversarial networks, synthesizing images from textual descriptions has recently become an active research area.
1 code implementation • 7 Jan 2021 • Sebastian Palacio, Philipp Engler, Jörn Hees, Andreas Dengel
Classification problems solved with deep neural networks (DNNs) typically rely on a closed world paradigm, and optimize over a single objective (e. g., minimization of the cross-entropy loss).
Ranked #89 on Image Classification on CIFAR-100 (using extra training data)
1 code implementation • 3 Dec 2020 • Vinu Joseph, Shoaib Ahmed Siddiqui, Aditya Bhaskara, Ganesh Gopalakrishnan, Saurav Muralidharan, Michael Garland, Sheraz Ahmed, Andreas Dengel
With the rise in edge-computing devices, there has been an increasing demand to deploy energy and resource-efficient models.
no code implementations • 26 Nov 2020 • Adriano Lucieri, Muhammad Naseer Bajwa, Andreas Dengel, Sheraz Ahmed
Remarkable success of modern image-based AI methods and the resulting interest in their applications in critical decision-making processes has led to a surge in efforts to make such intelligent systems transparent and explainable.
1 code implementation • 16 Nov 2020 • Markus Schröder, Christian Jilek, Michael Schulze, Andreas Dengel
First, we give a formal definition of the problem and describe a procedure to generate ground truth data for future evaluations.
no code implementations • LANTERN (COLING) 2020 • Stanislav Frolov, Shailza Jolly, Jörn Hees, Andreas Dengel
We create additional training samples by concatenating question and answer (QA) pairs and employ a standard VQA model to provide the T2I model with an auxiliary learning signal.
1 code implementation • 10 Oct 2020 • Fatemeh Azimi, Stanislav Frolov, Federico Raue, Joern Hees, Andreas Dengel
In this work, we study an RNN-based architecture and address some of these issues by proposing a hybrid sequence-to-sequence architecture named HS2S, utilizing a dual mask propagation strategy that allows incorporating the information obtained from correspondence matching.
no code implementations • 30 Aug 2020 • Shoaib Ahmed Siddiqui, Andreas Dengel, Sheraz Ahmed
This paves the way for future research in the direction of adversarial attacks and defenses, particularly for time-series data.
no code implementations • 18 Aug 2020 • Divya Gaur, Joachim Folz, Andreas Dengel
The main purpose of this work is to determine if it is possible to train networks effectively when batch normalization is removed through adaption of the training process.
no code implementations • 28 May 2020 • Muhammad Naseer Bajwa, Yoshinobu Taniguchi, Muhammad Imran Malik, Wolfgang Neumeier, Andreas Dengel, Sheraz Ahmed
Visual artefacts of early diabetic retinopathy in retinal fundus images are usually small in size, inconspicuous, and scattered all over retina.
no code implementations • 28 May 2020 • Muhammad Naseer Bajwa, Muhammad Imran Malik, Shoaib Ahmed Siddiqui, Andreas Dengel, Faisal Shafait, Wolfgang Neumeier, Sheraz Ahmed
For glaucoma classification we achieved AUC equal to 0. 874 which is 2. 7% relative improvement over the state-of-the-art results previously obtained for classification on ORIGA.
2 code implementations • 28 May 2020 • Muhammad Naseer Bajwa, Gur Amrit Pal Singh, Wolfgang Neumeier, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
Scarcity of large publicly available retinal fundus image datasets for automated glaucoma detection has been the bottleneck for successful application of artificial intelligence towards practical Computer-Aided Diagnosis (CAD).
1 code implementation • 5 May 2020 • Dominique Mercier, Syed Tahseen Raza Rizvi, Vikas Rajashekar, Andreas Dengel, Sheraz Ahmed
Therefore, citation impact analysis (which includes sentiment and intent classification) enables us to quantify the quality of the citations which can eventually assist us in the estimation of ranking and impact.
Ranked #1 on Citation Intent Classification on SciCite (using extra training data)
1 code implementation • 5 May 2020 • Dominique Mercier, Shoaib Ahmed Siddiqui, Andreas Dengel, Sheraz Ahmed
Identification of input data points relevant for the classifier (i. e. serve as the support vector) has recently spurred the interest of researchers for both interpretability as well as dataset debugging.
no code implementations • 5 May 2020 • Adriano Lucieri, Muhammad Naseer Bajwa, Stephan Alexander Braun, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
This work aims at elucidating a deep learning based medical image classifier by verifying that the model learns and utilizes similar disease-related concepts as described and employed by dermatologists.
no code implementations • 5 May 2020 • Dominique Mercier, Andreas Dengel, Sheraz Ahmed
Deep learning methods have shown great success in several domains as they process a large amount of data efficiently, capable of solving complex classification, forecast, segmentation, and other tasks.
1 code implementation • 4 May 2020 • Adriano Lucieri, Muhammad Naseer Bajwa, Andreas Dengel, Sheraz Ahmed
We evaluated our proposed method on SCDB as well as a real-world dataset called CelebA.
1 code implementation • 3 May 2020 • Alireza Koochali, Andreas Dengel, Sheraz Ahmed
The motivation of the framework is to either transform existing highly accurate point forecast models to their probabilistic counterparts or to train GANs stably by selecting the architecture of GAN's component carefully and efficiently.
Multivariate Time Series Forecasting Probabilistic Time Series Forecasting +1
1 code implementation • 25 Apr 2020 • Fatemeh Azimi, Benjamin Bischke, Sebastian Palacio, Federico Raue, Joern Hees, Andreas Dengel
Video Object Segmentation (VOS) is an active research area of the visual domain.
2 code implementations • 19 Apr 2020 • Mateus Dias Ribeiro, Abdul Rehman, Sheraz Ahmed, Andreas Dengel
Computational Fluid Dynamics (CFD) simulation by the numerical solution of the Navier-Stokes equations is an essential tool in a wide range of applications from engineering design to climate modeling.
1 code implementation • 15 Apr 2020 • Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
Environmental Sound Classification (ESC) is an active research area in the audio domain and has seen a lot of progress in the past years.
Ranked #5 on Environmental Sound Classification on UrbanSound8K (using extra training data)
no code implementations • ICLR 2020 • Shoaib Ahmed Siddiqui, Dominique Mercier, Andreas Dengel, Sheraz Ahmed
We approach the problem of interpretability in a novel way by proposing TSInsight where we attach an auto-encoder to the classifier with a sparsity-inducing norm on its output and fine-tune it based on the gradients from the classifier and a reconstruction penalty.
1 code implementation • 26 Mar 2020 • Shailza Jolly, Sebastian Palacio, Joachim Folz, Federico Raue, Joern Hees, Andreas Dengel
In recent years, progress in the Visual Question Answering (VQA) field has largely been driven by public challenges and large datasets.
no code implementations • 3 Mar 2020 • Muhammad Nabeel Asim, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Sheraz Ahmad, Waqar Mahmood, Andreas Dengel
Second, it investigates the performance impact of traditional machine learning based Urdu text document classification methodologies by embedding 10 filter-based feature selection algorithms which have been widely used for other languages.
no code implementations • 16 Dec 2019 • Syed Tahseen Raza Rizvi, Andreas Dengel, Sheraz Ahmed
DeepBiRD was evaluated on two different datasets to demonstrate the generalization of this approach.
no code implementations • 7 Oct 2019 • Dominique Mercier, Akansha Bhardwaj, Andreas Dengel, Sheraz Ahmed
This paper presents a novel system for sentiment analysis of citations in scientific documents (SentiCite) and is also capable of detecting nature of citations by targeting the motivation behind a citation, e. g., reference to a dataset, reading reference.
1 code implementation • 12 Sep 2019 • Muhammad Nabeel Asim, Muhammad Usman Ghani Khan, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
Evaluation results reveal that the proposed methodology outperforms the state-of-the-art of both the (traditional) machine learning and deep learning based text document classification methodologies with a significant margin of 7. 7% on 20 Newsgroups and 6. 6% on BBC news datasets.
1 code implementation • 26 May 2019 • Kumar Shridhar, Joonho Lee, Hideaki Hayashi, Purvanshi Mehta, Brian Kenji Iwana, Seokjun Kang, Seiichi Uchida, Sheraz Ahmed, Andreas Dengel
We show that ProbAct increases the classification accuracy by +2-3% compared to ReLU or other conventional activation functions on both original datasets and when datasets are reduced to 50% and 25% of the original size.
no code implementations • 15 May 2019 • Mohsin Munir, Shoaib Ahmed Siddiqui, Ferdinand Küsters, Dominique Mercier, Andreas Dengel, Sheraz Ahmed
This indicates a vital gap between the explainability provided by the systems and the novice user.
1 code implementation • 29 Mar 2019 • Alireza Koochali, Peter Schichtel, Sheraz Ahmed, Andreas Dengel
To investigate probabilistic forecasting of ForGAN, we create a new dataset and demonstrate our method abilities on it.
Generative Adversarial Network Probabilistic Time Series Forecasting +3
no code implementations • 14 Mar 2019 • Markus Schröder, Christian Jilek, Andreas Dengel
Semantic services (e. g. Semantic Desktops) are still afflicted by a cold start problem: in the beginning, the user's personal information sphere, i. e. files, mails, bookmarks, etc., is not represented by the system.
no code implementations • 15 Feb 2019 • Muhammad Ali Chattha, Shoaib Ahmed Siddiqui, Muhammad Imran Malik, Ludger van Elst, Andreas Dengel, Sheraz Ahmed
The promise of ANNs to automatically discover and extract useful features/patterns from data without dwelling on domain expertise although seems highly promising but comes at the cost of high reliance on large amount of accurately labeled data, which is often hard to acquire and formulate especially in time-series domains like anomaly detection, natural disaster management, predictive maintenance and healthcare.
no code implementations • 8 Jan 2019 • Philipp Blandfort, Tushar Karayil, Federico Raue, Jörn Hees, Andreas Dengel
In this paper, we run an experiment on movie ratings data, where we analyze the effect on embedding quality caused by several fusion strategies in neural networks.
3 code implementations • 19 Dec 2018 • Mohsin Munir, Shoaib Ahmed Siddiqui, Andreas Dengel, Sheraz Ahmed
In contrast to the anomaly detection methods where anomalies are learned, DeepAnT uses unlabeled data to capture and learn the data distribution that is used to forecast the normal behavior of a time series.
no code implementations • 5 Dec 2018 • Christian Jilek, Markus Schröder, Rudolf Novik, Sven Schwarz, Heiko Maus, Andreas Dengel
Since precision and recall are higher than with comparably fast methods, we conclude that the quality gap between high speed methods and sophisticated NLP pipelines can be narrowed a bit more without losing too much runtime performance.
no code implementations • 15 Oct 2018 • Tushar Karayil, Philipp Blandfort, Jörn Hees, Andreas Dengel
Subjective visual interpretation is a challenging yet important topic in computer vision.
no code implementations • 12 Sep 2018 • Shailza Jolly, Sandro Pezzelle, Tassilo Klein, Andreas Dengel, Moin Nabi
We show that our metric is effective in providing a more fine-grained evaluation both on the quantitative and qualitative level.
no code implementations • 9 Aug 2018 • Benjamin Bischke, Patrick Helber, Florian König, Damian Borth, Andreas Dengel
This assumption limits the applications of multi-modal models since in practice the data collection process is likely to generate data with missing, incomplete or corrupted modalities.
no code implementations • 2 Aug 2018 • Hiroki Ohashi, Mohammad Al-Naser, Sheraz Ahmed, Katsuyuki Nakamura, Takuto Sato, Andreas Dengel
ZSL classifies instances of unseen classes, from which no training data is available, by utilizing the attributes of the classes.
no code implementations • 13 Jun 2018 • Markus Schröder, Christian Jilek, Jörn Hees, Andreas Dengel
In the field of machine learning, data understanding is the practice of getting initial insights in unknown datasets.
no code implementations • 6 May 2018 • Christian Jilek, Markus Schröder, Sven Schwarz, Heiko Maus, Andreas Dengel
Existing Semantic Desktops are still reproached for being too complicated to use or not scaling well.
1 code implementation • CVPR 2018 • Sebastian Palacio, Joachim Folz, Jörn Hees, Federico Raue, Damian Borth, Andreas Dengel
To do this, an autoencoder (AE) was fine-tuned on gradients from a pre-trained classifier with fixed parameters.
Ranked #819 on Image Classification on ImageNet
no code implementations • 21 Mar 2018 • Joachim Folz, Sebastian Palacio, Joern Hees, Damian Borth, Andreas Dengel
We analyze their robustness against several white-box and gray-box scenarios on the large ImageNet dataset.
1 code implementation • 8 Feb 2018 • Shoaib Ahmed Siddiqui, Dominik Mercier, Mohsin Munir, Andreas Dengel, Sheraz Ahmed
This is a step towards making informed/explainable decisions in the domain of time-series, powered by deep learning.
1 code implementation • 18 Sep 2017 • Benjamin Bischke, Patrick Helber, Joachim Folz, Damian Borth, Andreas Dengel
In this paper, we address the problem of preserving semantic segmentation boundaries in high resolution satellite imagery by introducing a new cascaded multi-task loss.
4 code implementations • 15 Sep 2017 • Marco Schreyer, Timur Sattarov, Damian Borth, Andreas Dengel, Bernd Reimer
Learning to detect fraud in large-scale accounting data is one of the long-standing challenges in financial statement audits or fraud investigations.
8 code implementations • 31 Aug 2017 • Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth
We present a novel dataset based on Sentinel-2 satellite images covering 13 spectral bands and consisting out of 10 classes with in total 27, 000 labeled and geo-referenced images.
4 code implementations • 28 Oct 2016 • Brian Kenji Iwana, Syed Tahseen Raza Rizvi, Sheraz Ahmed, Andreas Dengel, Seiichi Uchida
Book covers communicate information to potential readers, but can that same information be learned by computers?
Ranked #1 on Genre classification on Book Cover Dataset
no code implementations • 3 Aug 2016 • Sebastian Baumbach, Frank Wittich, Florian Sachs, Sheraz Ahmed, Andreas Dengel
The existing approaches for site selection (commonly used by economists) are manual, subjective, and not scalable, especially to Big Data.
no code implementations • 25 Jul 2016 • Jörn Hees, Rouven Bauer, Joachim Folz, Damian Borth, Andreas Dengel
We show the scalability of the algorithm by running it against a SPARQL endpoint loaded with > 7. 9 billion triples.
no code implementations • 4 May 2016 • Sheraz Ahmed, Muhammad Imran Malik, Muhammad Zeshan Afzal, Koichi Kise, Masakazu Iwamura, Andreas Dengel, Marcus Liwicki
The method is generic, language independent and can be used for generation of labeled documents datasets (both scanned and cameracaptured) in any cursive and non-cursive language, e. g., English, Russian, Arabic, Urdu, etc.
no code implementations • 13 Nov 2015 • Federico Raue, Andreas Dengel, Thomas M. Breuel, Marcus Liwicki
We evaluated the proposed extension in the following scenarios: missing elements in one modality (visual or audio) and missing elements in both modalities (visual and sound).
3 code implementations • 17 Sep 2015 • Peter Burkert, Felix Trier, Muhammad Zeshan Afzal, Andreas Dengel, Marcus Liwicki
The proposed architecture achieves 99. 6% for CKP and 98. 63% for MMI, therefore performing better than the state of the art using CNNs.
Ranked #1 on Facial Expression Recognition (FER) on MMI