Neural networks : the official journal of the International Neural Network Society
May 22, 2020
Deep learning has received increasing attention in recent years and it has been successfully applied for feature extraction (FE) of hyperspectral images. However, most deep learning methods fail to explore the manifold structure in hyperspectral imag...
Neural networks : the official journal of the International Neural Network Society
May 21, 2020
Locality preserving projection (LPP), as a well-known technique for dimensionality reduction, is designed to preserve the local structure of the original samples which usually lie on a low-dimensional manifold in the real world. However, it suffers f...
Neural networks : the official journal of the International Neural Network Society
May 21, 2020
Deep neural networks have shown high performance in prediction, but they are defenseless when they predict on adversarial examples which are generated by adversarial attack techniques. In image classification, those attack techniques usually perturb ...
Neural networks : the official journal of the International Neural Network Society
May 19, 2020
Detecting the locations of multiple actions in videos and classifying them in real-time are challenging problems termed "action localization and prediction" problem. Convolutional neural networks (ConvNets) have achieved great success for action loca...
Neural networks : the official journal of the International Neural Network Society
May 15, 2020
The actuator of any physical control systems is constrained by amplitude and energy, which causes the control systems to be inevitably affected by actuator saturation. In this paper, impulsive synchronization of coupled delayed neural networks with a...
Spiking neural networks (SNN) are computational models inspired by the brain's ability to naturally encode and process information in the time domain. The added temporal dimension is believed to render them more computationally efficient than the con...
Literature-based Discovery (LBD) aims to discover new knowledge automatically from large collections of literature. Scientific literature is growing at an exponential rate, making it difficult for researchers to stay current in their discipline and e...
Neural networks : the official journal of the International Neural Network Society
May 8, 2020
Predicting salient regions in natural images requires the detection of objects that are present in a scene. To develop robust representations for this challenging task, high-level visual features at multiple spatial scales must be extracted and augme...
We developed an automatic method for staging periodontitis on dental panoramic radiographs using the deep learning hybrid method. A novel hybrid framework was proposed to automatically detect and classify the periodontal bone loss of each individual ...
Neural networks : the official journal of the International Neural Network Society
Apr 30, 2020
Due to their unprecedented capacity to learn patterns from raw data, deep neural networks have become the de facto modeling choice to address complex machine learning tasks. However, recent works have emphasized the vulnerability of deep neural netwo...