Video surveillance systems process high volumes of image data. To enable long-term retention of recorded images and because of the data transfer limitations in geographically distributed systems, lossy compression is commonly applied to images prior ...
Computational intelligence and neuroscience
Feb 1, 2022
The measurement of input and output torque of a precision reducer, the core component of an industrial robot, plays a vital role in evaluating the robot's performance. The TMSIS and TMSOS of a vertical cylindrical high-precision reducer detector were...
Apple tree diseases have perplexed orchard farmers for several years. At present, numerous studies have investigated deep learning for fruit and vegetable crop disease detection. Because of the complexity and variety of apple leaf veins and the diffi...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 1, 2022
Convolutional Neural Networks (CNN) and Graph Neural Networks (GNN), such as Graph Attention Networks (GAT), are two classic neural network models, which are applied to the processing of grid data and graph data respectively. They have achieved outst...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 1, 2022
Unsupervised domain adaptation (UDA) for person re-identification is challenging because of the huge gap between the source and target domain. A typical self-training method is to use pseudo-labels generated by clustering algorithms to iteratively op...
Computer methods in biomechanics and biomedical engineering
Jan 31, 2022
Nowadays, deep learning methods with transfer learning (TL) makes ease of stress emotion classification tasks. Amongst, an optimized convolutional neural network with TL (OCNNTL) executes OCNN-based classification on emotion and stress data domains t...
Elucidating the mechanisms of Compound-Protein Interactions (CPIs) plays an essential role in drug discovery and development. Many computational efforts have been done to accelerate the development of this field. However, the current predictive perfo...
How do neural populations code for multiple, potentially conflicting tasks? Here we used computational simulations involving neural networks to define "lazy" and "rich" coding solutions to this context-dependent decision-making problem, which trade o...
In this work, different types of artificial neural networks are investigated for the estimation of the time of arrival (ToA) in acoustic emission (AE) signals. In particular, convolutional neural network (CNN) models and a novel capsule neural networ...
Engineering pharmaceutical formulations is governed by a number of variables, and the finding of the optimal preparation is intricately linked to the exploration of a multiparametric space through a variety of optimization tasks. As a result, making ...
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