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Found 9 papers, 0 papers with code
Hierarchical Classification of Financial Transactions Through Context-Fusion of Transformer-based Embeddings and Taxonomy-aware Attention Layer
This work proposes the Two-headed DragoNet, a Transformer-based model for hierarchical multi-label classification of financial transactions.
Building a Noisy Audio Dataset to Evaluate Machine Learning Approaches for Automatic Speech Recognition Systems
Automatic speech recognition systems are part of people's daily lives, embedded in personal assistants and mobile phones, helping as a facilitator for human-machine interaction while allowing access to information in a practically intuitive way.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Generating Data Augmentation samples for Semantic Segmentation of Salt Bodies in a Synthetic Seismic Image Dataset
Our method uses deep learning models to generate pairs of seismic image patches and their respective salt masks for the Data Augmentation.
A Cluster-Matching-Based Method for Video Face Recognition
We propose a cluster-matching-based approach for face recognition in video.
A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers
Discovering and accessing specific content within educational video bases is a challenging task, mainly because of the abundance of video content and its diversity.
Video Quality Enhancement Using Deep Learning-Based Prediction Models for Quantized DCT Coefficients in MPEG I-frames
Recent works have successfully applied some types of Convolutional Neural Networks (CNNs) to reduce the noticeable distortion resulting from the lossy JPEG/MPEG compression technique.
Seismic Shot Gather Noise Localization Using a Multi-Scale Feature-Fusion-Based Neural Network
Herein, we describe the following: (1) the construction of a real-world dataset of seismic noise localization based on 6, 500 seismograms; (2) a multi-scale feature-fusion-based detector that uses the MobileNet combined with the Feature Pyramid Net as the backbone; and (3) the Single Shot multi-box detector for box classification/regression.
A Deep Convolutional Network for Seismic Shot-Gather Image Quality Classification
Deep Learning-based models such as Convolutional Neural Networks, have led to significant advancements in several areas of computing applications.
A Multimodal CNN-based Tool to Censure Inappropriate Video Scenes
More than telling if a video is either appropriate or inappropriate, it is also important to identify which parts of it contain such content, for preserving parts that would be discarded in a simple broad analysis.
