LAUSR

Local Learning With Deep and Handcrafted Features for Facial Expression Recognition

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1 Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2917266

Abstract: We present an approach that combines automatic features learned by convolutional neural networks (CNN) and handcrafted features computed by the bag-of-visual-words (BOVW) model in order to achieve the state-of-the-art results in facial expression recognition (FER).… read more here.

Keywords: handcrafted features; facial expression; expression recognition; local learning ... See more keywords

Deep Spike Learning With Local Classifiers

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2 Published in 2022 at "IEEE Transactions on Cybernetics"

DOI: 10.1109/tcyb.2022.3188015

Abstract: Backpropagation has been successfully generalized to optimize deep spiking neural networks (SNNs), where, nevertheless, gradients need to be propagated back through all layers, resulting in a massive consumption of computing resources and an obstacle to… read more here.

Keywords: learning local; spike learning; deep spike; local learning ... See more keywords

Community Detection via Local Learning Based on Generalized Metric With Neighboring Regularization

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1 Published in 2022 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"

DOI: 10.1109/tsmc.2020.3003019

Abstract: Community detection has long been a fundamental problem in network analysis. A great deal of previous research has regarded community detection as an optimization process, where a variety of internal quality metrics are typically treated… read more here.

Keywords: generalized metric; regularization; community; local learning ... See more keywords

Dynamic Block-Wise Local Learning Algorithm for Efficient Neural Network Training

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1 Published in 2021 at "IEEE Transactions on Very Large Scale Integration (VLSI) Systems"

DOI: 10.1109/tvlsi.2021.3097341

Abstract: In the backpropagation algorithm, the error calculated from the output of the neural network should backpropagate the layers to update the weights of each layer, making it difficult to parallelize the training process and requiring… read more here.

Keywords: block; neural network; learning algorithm; local learning ... See more keywords

Efficient Neuromorphic Hardware Through Spiking Temporal Online Local Learning

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1 Published in 2022 at "IEEE Transactions on Very Large Scale Integration (VLSI) Systems"

DOI: 10.1109/tvlsi.2022.3208191

Abstract: Local learning schemes have shown promising performance in spiking neural networks (SNNs) training and are considered a step toward more biologically plausible learning. Despite many efforts to design high-performance neuromorphic systems, a fast and efficient… read more here.

Keywords: neuromorphic hardware; hardware; training; local learning ... See more keywords