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Improved deep CNNs based on Nonlinear Hybrid Attention Module for image classification

期刊: NEURAL NETWORKS, 2021; 140 ()

Recent years have witnessed numerous successful applications of incorporating attention module into feed-forward convolutional neural networks. Along ......

Extracting and inserting knowledge into stacked denoising auto-encoders

期刊: NEURAL NETWORKS, 2021; 137 ()

Deep neural networks (DNNs) with a complex structure and multiple nonlinear processing units have achieved great successes for feature learning in ima......

A new recursive least squares-based learning algorithm for spiking neurons

期刊: NEURAL NETWORKS, 2021; 138 ()

Spiking neural networks (SNNs) are regarded as effective models for processing spatio-temporal information. However, their inherent complexity of temp......

Passive filter design for fractional-order quaternion-valued neural networks with neutral delays and external disturbance

期刊: NEURAL NETWORKS, 2021; 137 ()

The problem on passive filter design for fractional-order quaternion-valued neural networks (FOQVNNs) with neutral delays and external disturbance is ......

Cross Knowledge-based Generative Zero-Shot Learning approach with Taxonomy Regularization

期刊: NEURAL NETWORKS, 2021; 139 ()

Although zero-shot learning (ZSL) has an inferential capability of recognizing new classes that have never been seen before, it always faces two funda......

Stochastic quasi-synchronization of heterogeneous delayed impulsive dynamical networks via single impulsive control

期刊: NEURAL NETWORKS, 2021; 139 ()

This paper investigates the quasi-synchronization problem of the stochastic heterogeneous complex dynamical networks with impulsive couplings and mult......

A CNN model embedded with local feature knowledge and its application to time-varying signal classification

期刊: NEURAL NETWORKS, 2021; 142 ()

A novel convolutional neural network is proposed for local prior feature embedding and imbalanced dataset modeling for multi-channel time-varying sign......

Synchronization criteria of delayed inertial neural networks with generally Markovian jumping

期刊: NEURAL NETWORKS, 2021; 139 ()

In this paper, the synchronization problem of inertial neural networks with time-varying delays and generally Markovian jumping is investigated. The s......

TigeCMN: On exploration of temporal interaction graph embedding via Coupled Memory Neural Networks

期刊: NEURAL NETWORKS, 2021; 140 ()

With the increasing demand of mining rich knowledge in graph structured data, graph embedding has become one of the most popular research topics in bo......

Saturated impulsive control for synchronization of coupled delayed neural networks

期刊: NEURAL NETWORKS, 2021; 141 ()

The paper focuses on the synchronization problem for a class of coupled neural networks with impulsive control, where the saturation structure of impu......

Capturing the grouping and compactness of high-level semantic feature for saliency detection

期刊: NEURAL NETWORKS, 2021; 142 ()

Saliency detection is an important and challenging research topic due to the variety and complexity of the background and saliency regions. In this pa......

A noisy label and negative sample robust loss function for DNN-based distant supervised relation extraction

期刊: NEURAL NETWORKS, 2021; 139 ()

As a major method for relation extraction, distantly supervised relation extraction (DSRE) suffered from the noisy label problem and class imbalance p......

Speaker recognition based on deep learning: An overview

期刊: NEURAL NETWORKS, 2021; 140 ()

Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. H......

IHG-MA: Inductive heterogeneous graph multi-agent reinforcement learning for multi-intersection traffic signal control

期刊: NEURAL NETWORKS, 2021; 139 ()

Multi-agent deep reinforcement learning (MDRL) has been widely applied in multi-intersection traffic signal control. The MDRL algorithms produce the d......

Multi-resolution modulation-filtered cochleagram feature for LSTM-based dimensional emotion recognition from speech

期刊: NEURAL NETWORKS, 2021; 140 ()

Continuous dimensional emotion recognition from speech helps robots or virtual agents capture the temporal dynamics of a speaker's emotional state in ......

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