AIMC Topic: Pattern Recognition, Automated

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Adaptively Learning Facial Expression Representation via C-F Labels and Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jan 21, 2021
Facial expression recognition is of significant importance in criminal investigation and digital entertainment. Under unconstrained conditions, existing expression datasets are highly class-imbalanced, and the similarity between expressions is high. ...
Image Processing, Computer-Assisted Emotions Pattern Recognition, Automated Facial Expression Face Algorithms Databases, Factual Humans Machine Learning
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A conditional Triplet loss for few-shot learning and its application to image co-segmentation.

Neural networks : the official journal of the International Neural Network Society Jan 20, 2021
Few-shot learning tries to solve the problems that suffer the limited number of samples. In this paper we present a novel conditional Triplet loss for solving few-shot problems using deep metric learning. While the conventional Triplet loss suffers t...
Pattern Recognition, Automated Deep Learning Image Processing, Computer-Assisted
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Shallow Graph Convolutional Network for Skeleton-Based Action Recognition.

Sensors (Basel, Switzerland) Jan 11, 2021
Graph convolutional networks (GCNs) have brought considerable improvement to the skeleton-based action recognition task. Existing GCN-based methods usually use the fixed spatial graph size among all the layers. It severely affects the model's abiliti...
Humans Pattern Recognition, Automated Skeleton Neural Networks, Computer
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Visual behavior modelling for robotic theory of mind.

Scientific reports Jan 11, 2021
Behavior modeling is an essential cognitive ability that underlies many aspects of human and animal social behavior (Watson in Psychol Rev 20:158, 1913), and an ability we would like to endow robots. Most studies of machine behavior modelling, howeve...
Theory of Mind Robotics Pattern Recognition, Automated Visual Perception Computer Communication Networks Computer Simulation Animals Humans Machine Learning
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Few-Shot Human-Object Interaction Recognition With Semantic-Guided Attentive Prototypes Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jan 11, 2021
Extreme instance imbalance among categories and combinatorial explosion make the recognition of Human-Object Interaction (HOI) a challenging task. Few studies have addressed both challenges directly. Motivated by the success of few-shot learning that...
Machine Learning Animals Humans Semantics Pattern Recognition, Automated Image Processing, Computer-Assisted Attention
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Global and Local Knowledge-Aware Attention Network for Action Recognition.

IEEE transactions on neural networks and learning systems Jan 4, 2021
Convolutional neural networks (CNNs) have shown an effective way to learn spatiotemporal representation for action recognition in videos. However, most traditional action recognition algorithms do not employ the attention mechanism to focus on essent...
Humans Knowledge Movement Video Recording Pattern Recognition, Automated Reproducibility of Results Computer Systems Benchmarking Attention Image Processing, Computer-Assisted Algorithms Databases, Factual Neural Networks, Computer Machine Learning
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Gradients Cannot Be Tamed: Behind the Impossible Paradox of Blocking Targeted Adversarial Attacks.

IEEE transactions on neural networks and learning systems Jan 4, 2021
Despite their accuracy, neural network-based classifiers are still prone to manipulation through adversarial perturbations. These perturbations are designed to be misclassified by the neural network while being perceptually identical to some valid in...
Reproducibility of Results Pattern Recognition, Automated Classification Neural Networks, Computer Algorithms
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A Study of Multi-Task and Region-Wise Deep Learning for Food Ingredient Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Dec 31, 2020
Food recognition has captured numerous research attention for its importance for health-related applications. The existing approaches mostly focus on the categorization of food according to dish names, while ignoring the underlying ingredient composi...
China Humans Cooking Image Processing, Computer-Assisted Deep Learning Food Ingredients Pattern Recognition, Automated
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An enhanced approach to the robust discriminant analysis and class sparsity based embedding.

Neural networks : the official journal of the International Neural Network Society Dec 30, 2020
In recent times, feature extraction attracted much attention in machine learning and pattern recognition fields. This paper extends and improves a scheme for linear feature extraction that can be used in supervised multi-class classification problems...
Supervised Machine Learning Pattern Recognition, Automated Algorithms Discriminant Analysis Machine Learning
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Quantization Friendly MobileNet (QF-MobileNet) Architecture for Vision Based Applications on Embedded Platforms.

Neural networks : the official journal of the International Neural Network Society Dec 29, 2020
Deep Neural Networks (DNNs) have become popular for various applications in the domain of image and computer vision due to their well-established performance attributes. DNN algorithms involve powerful multilevel feature extractions resulting in an e...
Pattern Recognition, Automated Algorithms Photic Stimulation Memory Humans Deep Learning Neural Networks, Computer
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