WebIn this paper, we propose a novel particle swarm optimization (PSO) variant cPSO-CNN for optimizing the hyper-parameter configuration of architecture-determined CNNs. cPSO-CNN utilizes a confidence function defined by a compound normal distribution to model experts' knowledge on CNN hyper-parameter fine-tunings so as to enhance the canonical … WebSep 1, 2024 · In this paper, we propose a novel particle swarm optimization (PSO) variant cPSO-CNN for optimizing the hyper-parameter configuration of architecture-determined …
cPSO-CNN: An efficient PSO-based algorithm for fine-tuning
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cPSO-CNN: An efficient PSO-based algorithm for fine-tuning …
WebcPSO-CNN: An efficient PSO-based algorithm for fine-tuning hyper-parameters of convolutional neural networks Yulong Wang , Haoxin Zhang , Guangwei Zhang . Swarm … WebMar 5, 2024 · The values of Hough-cPSO-CNN illustrates greater classifying process with the accuracy of 98.01, sensitivity of 98.57 and specificity of 96.77. But, Standard CNN … WebAug 31, 2024 · In this paper, we propose a novel particle swarm optimization (PSO) variant cPSO-CNN for optimizing the hyper-parameter configuration of architecture-determined CNNs. cPSO-CNN utilizes a confidence function defined by a compound normal distribution to model experts' knowledge on CNN hyper-parameter fine-tunings so as to enhance the … robert channon family search