A Comparison Between Custom Activation Function With Existing Activation Function |
Author(s): |
| Patel Swapnil Shaileshbhai , Vishwakarma Government Engineering College, Chandkheda, Ahmedabad, India |
Keywords: |
| Custom Activation Functions, Existing Activation Functions, Convolutional Neural Networks, CNN, Deep Learning, Performance Comparison, Accuracy, Convergence Speed, Relu, Deep Learning, Computer Vision Tasks, Dataset, Model Architecture, Supervised Learning |
Abstract |
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This research paper investigates the performance and comparison of custom activation functions with existing activation functions in the context of convolutional neural network (CNN) models. The study explores the impact of different activation functions on various datasets and CNN architectures. In particular paper, seven custom activation functions and five existing activation functions are examined to evaluate their effectiveness in enhancing the learning capabilities of CNN models. According to this paper different dataset have different activation function give different accuracy or some custom activation function give good accuracy compare to existing function. |
Other Details |
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Paper ID: IJSRDV11I40145 Published in: Volume : 11, Issue : 4 Publication Date: 01/07/2023 Page(s): 100-106 |
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