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Found 11 papers, 1 papers with code
Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking
In recent years, visual tracking methods based on convolutional neural networks and Transformers have achieved remarkable performance and have been successfully applied in fields such as autonomous driving.
Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks
Most existing RGB-D semantic segmentation methods focus on the feature level fusion, including complex cross-modality and cross-scale fusion modules.
Multi-view Clustering via Unified Multi-kernel Learning and Matrix Factorization
Matrix factorization-based multi-view clustering methods impose orthogonal constraints on individual views.
Critical Review for One-class Classification: recent advances and the reality behind them
This paper offers a comprehensive review of one-class classification (OCC), examining the technologies and methodologies employed in its implementation.
In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Tracking
Deep learning-based methods monopolize the latest research in the field of thermal infrared (TIR) object tracking.
ClueReader: Heterogeneous Graph Attention Network for Multi-hop Machine Reading Comprehension
Multi-hop machine reading comprehension is a challenging task in natural language processing as it requires more reasoning ability across multiple documents.
Word Sense Disambiguation: A comprehensive knowledge exploitation framework
Word Sense Disambiguation (WSD) has been a basic and on-going issue since its introduction in natural language processing (NLP) community.
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Word Sense Disambiguation
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Cluster-based Zero-shot learning for multivariate data
Zero-Shot Learning (ZSL) is the task of predicting class that is not in the training data(target class).
Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Although numerous recent tracking approaches have made tremendous advances in the last decade, achieving high-performance visual tracking remains a challenge.
Siamese Attentional Keypoint Network for High Performance Visual Tracking
In this paper, we investigate the impacts of three main aspects of visual tracking, i. e., the backbone network, the attentional mechanism, and the detection component, and propose a Siamese Attentional Keypoint Network, dubbed SATIN, for efficient tracking and accurate localization.
Application of deep convolutional neural network for automated detection of myocardial infarction using ecg signals
In this study, we implemented a convolutional neural network (CNN) algorithm for the automated detection of a normal and MI ECG beats (with noise and without noise).
