AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 621 to 630 of 817 articles

Practical Time-Varying Formation Tracking for Second-Order Nonlinear Multiagent Systems With Multiple Leaders Using Adaptive Neural Networks.

IEEE transactions on neural networks and learning systems Apr 12, 2018
Practical time-varying formation tracking problems for second-order nonlinear multiagent systems with multiple leaders are investigated using adaptive neural networks (NNs), where the time-varying formation tracking error caused by time-varying exter...
Neural Networks, Computer Algorithms Humans Nonlinear Dynamics Computer Graphics Computer Simulation Time Factors
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Low-Complexity Approximate Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems Apr 10, 2018
In this paper, we present an approach for minimizing the computational complexity of the trained convolutional neural networks (ConvNets). The idea is to approximate all elements of a given ConvNet and replace the original convolutional filters and p...
Humans Neural Networks, Computer Linear Models Pattern Recognition, Automated Algorithms Signal Processing, Computer-Assisted
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Runtime Programmable and Memory Bandwidth Optimized FPGA-Based Coprocessor for Deep Convolutional Neural Network.

IEEE transactions on neural networks and learning systems Apr 9, 2018
The deep convolutional neural network (DCNN) is a class of machine learning algorithms based on feed-forward artificial neural network and is widely used for image processing applications. Implementation of DCNN in real-world problems needs high comp...
Models, Neurological Signal Processing, Computer-Assisted Algorithms Computer Simulation Memory Humans Neural Networks, Computer Machine Learning Software
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Robust Regression Estimation Based on Low-Dimensional Recurrent Neural Networks.

IEEE transactions on neural networks and learning systems Apr 9, 2018
The robust Huber's M-estimator is widely used in signal and image processing, classification, and regression. From an optimization point of view, Huber's M-estimation problem is often formulated as a large-sized quadratic programming (QP) problem in ...
Regression Analysis Algorithms Signal Processing, Computer-Assisted Models, Neurological Humans Neural Networks, Computer
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Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems Mar 9, 2018
Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems. However, the successful application of these methods in motor imagery (MI) brain-compu...
Brain-Computer Interfaces Imagination Signal Processing, Computer-Assisted Pattern Recognition, Automated Algorithms Humans Learning Brain Neural Networks, Computer Electroencephalography
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Biologically Inspired Intensity and Depth Image Edge Extraction.

IEEE transactions on neural networks and learning systems Feb 20, 2018
In recent years, artificial vision research has moved from focusing on the use of only intensity images to include using depth images, or RGB-D combinations due to the recent development of low-cost depth cameras. However, depth images require a lot ...
Models, Neurological Action Potentials Neurons Pattern Recognition, Automated Virtual Reality Image Processing, Computer-Assisted Humans Neural Networks, Computer Depth Perception Visual Pathways
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On the Generalization Ability of Online Gradient Descent Algorithm Under the Quadratic Growth Condition.

IEEE transactions on neural networks and learning systems Jan 17, 2018
Online learning has been successfully applied in various machine learning problems. Conventional analysis of online learning achieves a sharp generalization bound with a strongly convex assumption. In this paper, we study the generalization ability o...
Humans Neural Networks, Computer Machine Learning Education, Distance Algorithms Generalization, Psychological
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Rank-One Matrix Completion With Automatic Rank Estimation via L1-Norm Regularization.

IEEE transactions on neural networks and learning systems Dec 11, 2017
Completing a matrix from a small subset of its entries, i.e., matrix completion is a challenging problem arising from many real-world applications, such as machine learning and computer vision. One popular approach to solve the matrix completion prob...
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Marginal Representation Learning With Graph Structure Self-Adaptation.

IEEE transactions on neural networks and learning systems Dec 4, 2017
Learning discriminative feature representations has shown remarkable importance due to its promising performance for machine learning problems. This paper presents a discriminative data representation learning framework by employing a simple yet powe...
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Deep Learning in Microscopy Image Analysis: A Survey.

IEEE transactions on neural networks and learning systems Nov 22, 2017
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerging as a l...
Image Processing, Computer-Assisted Male Deep Learning Humans Algorithms Surveys and Questionnaires Diagnosis, Computer-Assisted Microscopy Neural Networks, Computer Female
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