AIMC Topic: Learning

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A Survey of Sim-to-Real Transfer Techniques Applied to Reinforcement Learning for Bioinspired Robots.

IEEE transactions on neural networks and learning systems Jul 6, 2023
The state-of-the-art reinforcement learning (RL) techniques have made innumerable advancements in robot control, especially in combination with deep neural networks (DNNs), known as deep reinforcement learning (DRL). In this article, instead of revie...
Neural Networks, Computer Learning Robotics Reinforcement, Psychology
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Spatial-Spectral Unified Adaptive Probability Graph Convolutional Networks for Hyperspectral Image Classification.

IEEE transactions on neural networks and learning systems Jul 6, 2023
In hyperspectral image (HSI) classification task, semisupervised graph convolutional network (GCN)-based methods have received increasing attention. However, two problems still need to be addressed. The first is that the initial graph structure in th...
Neural Networks, Computer Learning Sample Size Benchmarking Probability
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Enhanced regularization for on-chip training using analog and temporary memory weights.

Neural networks : the official journal of the International Neural Network Society Jul 5, 2023
In-memory computing techniques are used to accelerate artificial neural network (ANN) training and inference tasks. Memory technology and architectural innovations allow efficient matrix-vector multiplications, gradient calculations, and updates to n...
Neural Networks, Computer Algorithms Learning Cognition Recognition, Psychology
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Evaluation of 5G and Fixed-Satellite Service Earth Station (FSS-ES) Downlink Interference Based on Artificial Neural Network Learning Models (ANN-LMS).

Sensors (Basel, Switzerland) Jul 5, 2023
Fifth-generation (5G) networks have been deployed alongside fourth-generation networks in high-traffic areas. The most recent 5G mobile communication access technology includes mmWave and sub-6 GHz C-bands. However, 5G signals possibly interfere with...
Neural Networks, Computer Computer Simulation Learning Information Technology
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Towards Adversarial Robustness for Multi-Mode Data through Metric Learning.

Sensors (Basel, Switzerland) Jul 5, 2023
Adversarial attacks have become one of the most serious security issues in widely used deep neural networks. Even though real-world datasets usually have large intra-variations or multiple modes, most adversarial defense methods, such as adversarial ...
Neural Networks, Computer Learning
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Cross-Domain Indoor Visual Place Recognition for Mobile Robot via Generalization Using Style Augmentation.

Sensors (Basel, Switzerland) Jul 4, 2023
The article presents an algorithm for the multi-domain visual recognition of an indoor place. It is based on a convolutional neural network and style randomization. The authors proposed a scene classification mechanism and improved the performance of...
Neural Networks, Computer Algorithms Learning Robotics Lighting
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Domain Adaptation Based on Semi-Supervised Cross-Domain Mean Discriminative Analysis and Kernel Transfer Extreme Learning Machine.

Sensors (Basel, Switzerland) Jul 2, 2023
Good data feature representation and high precision classifiers are the key steps for pattern recognition. However, when the data distributions between testing samples and training samples do not match, the traditional feature extraction methods and ...
Machine Learning Algorithms Learning Acclimatization
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Network Security Situation Prediction Based on Optimized Clock-Cycle Recurrent Neural Network for Sensor-Enabled Networks.

Sensors (Basel, Switzerland) Jul 1, 2023
We propose an optimized Clockwork Recurrent Neural Network (CW-RNN) based approach to address temporal dynamics and nonlinearity in network security situations, improving prediction accuracy and real-time performance. By leveraging the clock-cycle RN...
Neural Networks, Computer Algorithms Learning Memory, Long-Term
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Discriminative ensemble meta-learning with co-regularization for rare fundus diseases diagnosis.

Medical image analysis Jun 30, 2023
Deep neural networks (DNNs) have been widely applied in the medical image community, contributing to automatic ophthalmic screening systems for some common diseases. However, the incidence of fundus diseases patterns exhibits a typical long-tailed di...
Humans Neural Networks, Computer Learning Fundus Oculi Rare Diseases
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A continuation method for image registration based on dynamic adaptive kernel.

Neural networks : the official journal of the International Neural Network Society Jun 30, 2023
Image registration is a fundamental problem in computer vision and robotics. Recently, learning-based image registration methods have made great progress. However, these methods are sensitive to abnormal transformation and have insufficient robustnes...
Learning Image Processing, Computer-Assisted Robotics Generalization, Psychological
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