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A systematic review on overfitting control in shallow and deep neural networks
Shallow neural networks process the features directly, while deep networks extract features
automatically along with the training. Both models suffer from overfitting or poor …
automatically along with the training. Both models suffer from overfitting or poor …
[HTML][HTML] A review on dropout regularization approaches for deep neural networks within the scholarly domain
Dropout is one of the most popular regularization methods in the scholarly domain for
preventing a neural network model from overfitting in the training phase. Develo** an …
preventing a neural network model from overfitting in the training phase. Develo** an …
Pruning for compression of visual pattern recognition networks: a survey from deep neural networks perspective
Abstract Visual Pattern Recognition Networks (VPRN) delivers high performance using deep
neural networks. With the advancements in deep neural networks VPR network has gained …
neural networks. With the advancements in deep neural networks VPR network has gained …
Optimized tongue driven system using artificial intelligence
This paper presents a cost-effective design of a wearable wireless tongue drive system
(TDS) for disabled individuals, particularly with spinal cord injuries. We propose a basic TDS …
(TDS) for disabled individuals, particularly with spinal cord injuries. We propose a basic TDS …
[การอ้างอิง][C] Optimization of AI Methods on Distributed-Memory Computing Architectures
D Coquelin - 2024 - Blekinge Institute of Technology