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Found 3 papers, 2 papers with code
Target Aware Network Architecture Search and Compression for Efficient Knowledge Transfer
Later, in the second stage, the redundant filters are pruned from the fine-tuned CNN to decrease the network's complexity for the target task while preserving the performance.
AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer Learning
The experimental results obtained in this study depict that tuning of the pre-trained CNN layers with the knowledge from the target dataset confesses better transfer learning ability.
AutoFCL: Automatically Tuning Fully Connected Layers for Handling Small Dataset
Fine-tuning the newly learned (target-dependent) FC layers leads to state-of-the-art performance, according to the experiments carried out in this research.
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