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Found 34 papers, 8 papers with code
BdSLW60: A Word-Level Bangla Sign Language Dataset
Sign language discourse is an essential mode of daily communication for the deaf and hard-of-hearing people.
Towards Automated Recipe Genre Classification using Semi-Supervised Learning
Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation.
Multi-scale, Data-driven and Anatomically Constrained Deep Learning Image Registration for Adult and Fetal Echocardiography
We propose a framework that combines three strategies for DLIR in both fetal and adult echo: (1) an anatomic shape-encoded loss to preserve physiological myocardial and left ventricular anatomical topologies in warped images; (2) a data-driven loss that is trained adversarially to preserve good image texture features in warped images; and (3) a multi-scale training scheme of a data-driven and anatomically constrained algorithm to improve accuracy.
Assorted, Archetypal and Annotated Two Million (3A2M) Cooking Recipes Dataset based on Active Learning
In this study, we present a novel dataset of two million culinary recipes labeled in respective categories leveraging the knowledge of food experts and an active learning technique.
A Deep Learning Approach for Parallel Imaging and Compressed Sensing MRI Reconstruction
Parallel imaging and compressed sensing (CS) both reduce the amount of data captured in the k-space, which speeds up traditional MRI acquisition.
A survey, review, and future trends of skin lesion segmentation and classification
The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion analysis is an emerging field of research that has the potential to alleviate the burden and cost of skin cancer screening.
Learning Audio Representations with MLPs
In this paper, we propose an efficient MLP-based approach for learning audio representations, namely timestamp and scene-level audio embeddings.
Bangla sign digits recognition using depth information
The existing dataset for Sign Language Recognition (SLR) in Bangla Sign Language (BdSL) is based on RGB images.
VIS-iTrack: Visual Intention through Gaze Tracking using Low-Cost Webcam
From interactive interfaces containing either textual or graphical information, intention to perceive desired information is subjective and strongly connected with eye gaze.
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor.
A Case Study on the Independence of Speech Emotion Recognition in Bangla and English Languages using Language-Independent Prosodic Features
We employed three Emotional Speech Sets (ESS), of which the first two were developed by native Bengali speakers in Bangla and English languages separately.
A Deep Learning-based Multimodal Depth-Aware Dynamic Hand Gesture Recognition System
In this paper, we revisit this approach to hand gesture recognition and suggest several improvements.
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods
However, English is the predominant language for online resources and technical knowledge, journals, and documentation.
Acute Lymphoblastic Leukemia Detection from Microscopic Images Using Weighted Ensemble of Convolutional Neural Networks
We explore the weighted ensemble of different deep CNNs to recommend a better ALL cell classifier.
COVID-19 identification from volumetric chest CT scans using a progressively resized 3D-CNN incorporating segmentation, augmentation, and class-rebalancing
The novel COVID-19 is a global pandemic disease overgrowing worldwide.
Multi-class probabilistic atlas-based whole heart segmentation method in cardiac CT and MRI
Accurate and robust whole heart substructure segmentation is crucial in developing clinical applications, such as computer-aided diagnosis and computer-aided surgery.
Dermo-DOCTOR: A framework for concurrent skin lesion detection and recognition using a deep convolutional neural network with end-to-end dual encoders
For the recognition sub-network, the outputs of three fully connected layers, utilizing feature maps of two encoders and FFM, are aggregated to obtain a final lesion class.
L2-Constrained RemNet for Camera Model Identification and Image Manipulation Detection
Furthermore, we attain an overall accuracy of 99. 68% in image manipulation detection, which implies that it can be used as a general-purpose network for image forensic tasks.
CVR-Net: A deep convolutional neural network for coronavirus recognition from chest radiography images
Our source codes and model are publicly available at https://github. com/kamruleee51/CVR-Net.
DFR-TSD: A Deep Learning Based Framework for Robust Traffic Sign Detection Under Challenging Weather Conditions
However, the SOTA (SOTA) methods have been evaluated on clean and challenge-free datasets and overlooked the performance deterioration associated with different challenging conditions (CCs) that obscure the traffic images captured in the wild.
Multiframe-based Adaptive Despeckling Algorithm for Ultrasound B-mode Imaging with Superior Edge and Texture
In this paper, we propose a multiframe-based adaptive despeckling (MADS) algorithm to reconstruct a high-resolution B-mode image from raw radio-frequency (RF) data that is based on a multiple input single output (MISO) model.
A Novel Technique of Noninvasive Hemoglobin Level Measurement Using HSV Value of Fingertip Image
We generate two input feature matrices based on observation of two different data sets.
Integrating Multimodal Information in Large Pretrained Transformers
It does so by generating a shift to internal representation of BERT and XLNet; a shift that is conditioned on the visual and acoustic modalities.
DSNet: Automatic Dermoscopic Skin Lesion Segmentation
We evaluate our proposed model on two publicly available datasets, namely ISIC-2017 and PH2.
Automatic Mass Detection in Breast Using Deep Convolutional Neural Network and SVM Classifier
Pre-trained VGG19 network is used to extract features which are then followed by bagged decision tree for features selection and then a Support Vector Machine (SVM) classifier is trained and used for classifying between the mass and non-mass.
A Causality-Guided Prediction of the TED Talk Ratings from the Speech-Transcripts using Neural Networks
Automated prediction of public speaking performance enables novel systems for tutoring public speaking skills.
UR-FUNNY: A Multimodal Language Dataset for Understanding Humor
The dataset and accompanying studies, present a framework in multimodal humor detection for the natural language processing community.
Comparative Analysis of Automatic Skin Lesion Segmentation with Two Different Implementations
The contribution of this paper is to present and compare two different approaches to skin lesion segmentation.
Brain Tissue Segmentation Using NeuroNet With Different Pre-processing Techniques
The outcome of the research indicates that for the IBSR18 data-set, pre-processing and proper tuning of hyper-parameters for NeuroNet model have improvement in DSC for the brain tissue segmentation.
Quantification of Trabeculae Inside the Heart from MRI Using Fractal Analysis
For analysis cardiac functionality, extracting information from the Left ventricular (LV) is already a broad field of Medical Imaging.
Improving Facial Analysis and Performance Driven Animation through Disentangling Identity and Expression
We use a weakly-supervised approach in which identity labels are used to learn the different factors of variation linked to identity separately from factors related to expression.
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation
We examine a new form of smooth approximation to the zero one loss in which learning is performed using a reformulation of the widely used logistic function.
An Improved ACS Algorithm for the Solutions of Larger TSP Problems
Solving large traveling salesman problem (TSP) in an efficient way is a challenging area for the researchers of computer science.
