In the last step, the Neuromodulated Dopamine Hebbian Transfer Learning algorithm has been applied to fine-tune the weights. Figure 1. Flow chart of the NDHTL algorithm prediction of image classification based on deep learning. The Hebbian principles are used with a heterogeneous source and ...
In the last step, the Neuromodulated Dopamine Hebbian Transfer Learning algorithm has been applied to fine-tune the weights. Figure 1. Flow chart of the NDHTL algorithm prediction of image classification based on deep learning. The Hebbian principles are used with a heterogeneous source and ...
Overall, this underscores that the BERT–GCN–Transfer Learning model, integrating BERT’s robust text representation capabilities with GCN’s (Graph Convolutional Network) advantages in graph-structured data, achieves enhanced performance through transfer learning and fine-tuning on the target dataset. (...
New fine-tuning methods need to be researched to improve the learning policies and minimize the difference between the real world and the simulation. Finally, one of the major issues that was mentioned in the selected papers was negative transfer. The primary goal of using transfer learning is ...
Multilevel Fine Fault Diagnosis Method for Motors Based on Feature Extraction of Fractional Fourier Transform. Sensors 2022, 22, 1310. [Google Scholar] [CrossRef] [PubMed] Yan, X.; Liu, Y.; Jia, M. A Fault Diagnosis Approach for Rolling Bearing Integrated SGMD, IMSDE and Multiclass ...
After the fine-tuning of the pre-trained CNN models by the whale-call training dataset, the validation dataset is used to evaluate the performance of the proposed approach. Given 16 whale pods to be classified, a one-dimensional likelihood vector with a size of 1 × 16 would be the output...
The VGG19 network was designed as the basic backbone of our new network. The first 15 layers of the network were non-trainable frozen layers, while the four layers of the bottom network were used to conduct fine-tuning on the training dataset in the paper. Additionally, the loss function ...