AIMC Topic: Learning
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CSAC-Net: Fast Adaptive sEMG Recognition through Attention Convolution Network and Model-Agnostic Meta-Learning.
Sensors (Basel, Switzerland)
May 11, 2022
Gesture recognition through surface electromyography (sEMG) provides a new method for the control algorithm of bionic limbs, which is a promising technology in the field of human-computer interaction. However, subject specificity of sEMG along with t...
A Feed-Forward Neural Network for Increasing the Hopfield-Network Storage Capacity.
International journal of neural systems
May 6, 2022
In the hippocampal dentate gyrus (DG), pattern separation mainly depends on the concepts of 'expansion recoding', meaning random mixing of different DG input channels. However, recent advances in neurophysiology have challenged the theory of pattern ...
Cascaded Parsing of Human-Object Interaction Recognition.
IEEE transactions on pattern analysis and machine intelligence
May 5, 2022
This paper addresses the task of detecting and recognizing human-object interactions (HOI) in images. Considering the intrinsic complexity and structural nature of the task, we introduce a cascaded parsing network (CP-HOI) for a multi-stage, structur...
Joint Feature Synthesis and Embedding: Adversarial Cross-Modal Retrieval Revisited.
IEEE transactions on pattern analysis and machine intelligence
May 5, 2022
Recently, generative adversarial network (GAN) has shown its strong ability on modeling data distribution via adversarial learning. Cross-modal GAN, which attempts to utilize the power of GAN to model the cross-modal joint distribution and to learn c...
Spatiotemporal neural network with attention mechanism for El Niño forecasts.
Scientific reports
May 3, 2022
To learn spatiotemporal representations and anomaly predictions from geophysical data, we propose STANet, a spatiotemporal neural network with a trainable attention mechanism, and apply it to El Niño predictions for long-lead forecasts. The STANet ma...
Brain-Inspired Experience Reinforcement Model for Bin Packing in Varying Environments.
IEEE transactions on neural networks and learning systems
May 2, 2022
Bin-packing problem (BPP) is a typical combinatorial optimization problem whose decision-making process is NP-hard. This article examines BPPs in varying environments, where random number and shape of items are to be packed in different instances. Th...
Triple-Memory Networks: A Brain-Inspired Method for Continual Learning.
IEEE transactions on neural networks and learning systems
May 2, 2022
Continual acquisition of novel experience without interfering with previously learned knowledge, i.e., continual learning, is critical for artificial neural networks, while limited by catastrophic forgetting. A neural network adjusts its parameters w...
A Brain-Inspired Approach for Collision-Free Movement Planning in the Small Operational Space.
IEEE transactions on neural networks and learning systems
May 2, 2022
In a small operational space, e.g., mesoscale or microscale, we need to control movements carefully because of fragile objects. This article proposes a novel structure based on spiking neural networks to imitate the joint function of multiple brain r...
Memory Recall: A Simple Neural Network Training Framework Against Catastrophic Forgetting.
IEEE transactions on neural networks and learning systems
May 2, 2022
It is widely acknowledged that biological intelligence is capable of learning continually without forgetting previously learned skills. Unfortunately, it has been widely observed that many artificial intelligence techniques, especially (deep) neural ...
Robust Facial Landmark Detection by Multiorder Multiconstraint Deep Networks.
IEEE transactions on neural networks and learning systems
May 2, 2022
Recently, heatmap regression has been widely explored in facial landmark detection and obtained remarkable performance. However, most of the existing heatmap regression-based facial landmark detection methods neglect to explore the high-order feature...
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