AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 291 to 300 of 780 articles

General Bitwidth Assignment for Efficient Deep Convolutional Neural Network Quantization.

IEEE transactions on neural networks and learning systems Oct 5, 2022
Model quantization is essential to deploy deep convolutional neural networks (DCNNs) on resource-constrained devices. In this article, we propose a general bitwidth assignment algorithm based on theoretical analysis for efficient layerwise weight and...
Neural Networks, Computer Algorithms
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Training-Free Deep Generative Networks for Compressed Sensing of Neural Action Potentials.

IEEE transactions on neural networks and learning systems Oct 5, 2022
Energy consumption is an important issue for resource-constrained wireless neural recording applications with limited data bandwidth. Compressed sensing (CS) is a promising framework for addressing this challenge because it can compress data in an en...
Neural Networks, Computer Action Potentials
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Multigraph Transformer for Free-Hand Sketch Recognition.

IEEE transactions on neural networks and learning systems Oct 5, 2022
Learning meaningful representations of free-hand sketches remains a challenging task given the signal sparsity and the high-level abstraction of sketches. Existing techniques have focused on exploiting either the static nature of sketches with convol...
Neural Networks, Computer
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Two-Stage Bayesian Optimization for Scalable Inference in State-Space Models.

IEEE transactions on neural networks and learning systems Oct 5, 2022
State-space models (SSMs) are a rich class of dynamical models with a wide range of applications in economics, healthcare, computational biology, robotics, and more. Proper analysis, control, learning, and decision-making in dynamical systems modeled...
Neural Networks, Computer Computational Biology Bayes Theorem Probability Space Simulation
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A Deeply Supervised Convolutional Neural Network for Pavement Crack Detection With Multiscale Feature Fusion.

IEEE transactions on neural networks and learning systems Sep 1, 2022
Automatic crack detection is vital for efficient and economical road maintenance. With the explosive development of convolutional neural networks (CNNs), recent crack detection methods are mostly based on CNNs. In this article, we propose a deeply su...
Neural Networks, Computer Image Processing, Computer-Assisted
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Finite-Time Synchronization of Reaction-Diffusion Inertial Memristive Neural Networks via Gain-Scheduled Pinning Control.

IEEE transactions on neural networks and learning systems Aug 31, 2022
For the considered reaction-diffusion inertial memristive neural networks (IMNNs), this article proposes a novel gain-scheduled generalized pinning control scheme, where three pinning control strategies are involved and 2 controller gains can be sche...
Neural Networks, Computer Time Factors Diffusion
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BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture.

IEEE transactions on neural networks and learning systems Aug 31, 2022
Efficient neural architecture search (ENAS) achieves novel efficiency for learning architecture with high-performance via parameter sharing and reinforcement learning (RL). In the phase of architecture search, ENAS employs deep scalable architecture ...
Neural Networks, Computer Machine Learning Learning Reinforcement, Psychology
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DeepKeyGen: A Deep Learning-Based Stream Cipher Generator for Medical Image Encryption and Decryption.

IEEE transactions on neural networks and learning systems Aug 31, 2022
The need for medical image encryption is increasingly pronounced, for example, to safeguard the privacy of the patients' medical imaging data. In this article, a novel deep learning-based key generation network (DeepKeyGen) is proposed as a stream ci...
Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted
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Decision-Tree-Initialized Dendritic Neuron Model for Fast and Accurate Data Classification.

IEEE transactions on neural networks and learning systems Aug 31, 2022
This work proposes a decision tree (DT)-based method for initializing a dendritic neuron model (DNM). Neural networks become larger and larger, thus consuming more and more computing resources. This calls for a strong need to prune neurons that do no...
Neural Networks, Computer Algorithms Support Vector Machine Decision Trees Neurons
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Memory Attention Networks for Skeleton-Based Action Recognition.

IEEE transactions on neural networks and learning systems Aug 31, 2022
Skeleton-based action recognition has been extensively studied, but it remains an unsolved problem because of the complex variations of skeleton joints in 3-D spatiotemporal space. To handle this issue, we propose a newly temporal-then-spatial recali...
Neural Networks, Computer Skeleton
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