AIMC Journal:
IEEE transactions on neural networks and learning systems
Showing 781 to 790 of 817 articles
Single Hidden Layer Neural Networks With Random Weights Based on Nondifferentiable Functions.
IEEE transactions on neural networks and learning systems
May 14, 2025
Computational algorithms that utilize nondifferentiable functions have proven highly effective in machine learning applications. This study introduces a novel framework for incorporating nondifferentiable functions into the objective functions of ran...
Online Reinforcement Learning Control Designs With Acceleration Mechanism for Unknown Multiagent Systems Through Value Iteration.
IEEE transactions on neural networks and learning systems
May 14, 2025
In this article, an online reinforcement learning (RL) control method through value iteration (VI) is developed to solve the optimal cooperative control problem for the unknown linear discrete-time multiagent systems (MASs). On the one hand, an onlin...
Proportional-Integral-Observer-Based Fusion Estimation for Artificial Neural Networks: Implementing a One-Bit Encoding Scheme.
IEEE transactions on neural networks and learning systems
May 9, 2025
This article is concerned with the proportional-integral-observer (PIO)-based fusion estimation problem for a class of artificial neural networks (ANNs) equipped with multiple sensors, which are constrained by bandwidth and subjected to unknown-but-b...
Chest X-Ray Visual Saliency Modeling: Eye-Tracking Dataset and Saliency Prediction Model.
IEEE transactions on neural networks and learning systems
May 8, 2025
Radiologists' eye movements during medical image interpretation reflect their perceptual-cognitive processes of diagnostic decisions. The eye movement data can be modeled to represent clinically relevant regions in a medical image and potentially int...
Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery.
IEEE transactions on neural networks and learning systems
Mar 1, 2025
Predicting the pharmacological activity, toxicity, and pharmacokinetic properties of molecules is a central task in drug discovery. Existing machine learning methods are transferred from one resource rich molecular property to another data scarce pro...
Person Reidentification via Structural Deep Metric Learning.
IEEE transactions on neural networks and learning systems
Oct 1, 2019
Despite the promising progress made in recent years, person reidentification (re-ID) remains a challenging task due to the complex variations in human appearances from different camera views. This paper proposes to tackle this task by jointly learnin...
Action-Driven Visual Object Tracking With Deep Reinforcement Learning.
IEEE transactions on neural networks and learning systems
Jun 1, 2018
In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control track...
Multisource Transfer Double DQN Based on Actor Learning.
IEEE transactions on neural networks and learning systems
Jun 1, 2018
Deep reinforcement learning (RL) comprehensively uses the psychological mechanisms of "trial and error" and "reward and punishment" in RL as well as powerful feature expression and nonlinear mapping in deep learning. Currently, it plays an essential ...
Applications of Deep Learning and Reinforcement Learning to Biological Data.
IEEE transactions on neural networks and learning systems
Jun 1, 2018
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine ...
Person Re-identification by Multi-hypergraph Fusion.
IEEE transactions on neural networks and learning systems
Nov 1, 2017
Matching people across nonoverlapping cameras, also known as person re-identification, is an important and challenging research topic. Despite its great demand in many crucial applications such as surveillance, person re-identification is still far f...
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