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Pattern Recognition, Automated

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Global and Local Knowledge-Aware Attention Network for Action Recognition.

IEEE transactions on neural networks and learning systems
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...

Gradients Cannot Be Tamed: Behind the Impossible Paradox of Blocking Targeted Adversarial Attacks.

IEEE transactions on neural networks and learning systems
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...

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
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...

An enhanced approach to the robust discriminant analysis and class sparsity based embedding.

Neural networks : the official journal of the International Neural Network Society
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...

Quantization Friendly MobileNet (QF-MobileNet) Architecture for Vision Based Applications on Embedded Platforms.

Neural networks : the official journal of the International Neural Network Society
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...

Multiparameter Space Decision Voting and Fusion Features for Facial Expression Recognition.

Computational intelligence and neuroscience
Obtaining a valid facial expression recognition (FER) method is still a research hotspot in the artificial intelligence field. In this paper, we propose a multiparameter fusion feature space and decision voting-based classification for facial express...

Self-organized operational neural networks for severe image restoration problems.

Neural networks : the official journal of the International Neural Network Society
Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become the go-to methodology for tackling image restoration and has outperfo...

Generative Restricted Kernel Machines: A framework for multi-view generation and disentangled feature learning.

Neural networks : the official journal of the International Neural Network Society
This paper introduces a novel framework for generative models based on Restricted Kernel Machines (RKMs) with joint multi-view generation and uncorrelated feature learning, called Gen-RKM. To enable joint multi-view generation, this mechanism uses a ...

Histogram of Oriented Gradient-Based Fusion of Features for Human Action Recognition in Action Video Sequences.

Sensors (Basel, Switzerland)
Human Action Recognition (HAR) is the classification of an action performed by a human. The goal of this study was to recognize human actions in action video sequences. We present a novel feature descriptor for HAR that involves multiple features and...

KGen: a knowledge graph generator from biomedical scientific literature.

BMC medical informatics and decision making
BACKGROUND: Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new knowledge requires computational ...