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Fine-Tuning ResNeXt-50 for Deepfake Detection by gowrijaswanth31 is a document available to read on EtoBox.

The document outlines the methodology and considerations involved in fine-tuning a ResNeXt-50 model for deepfake detection, including dataset preparation, performance evaluation metrics, and strategies to address class imbalance and overfitting. It discusses the integration of a BiLSTM layer for sequential processing, the computational challenges faced, and the ethical implications of deploying deepfake detection technology. Additionally, it covers user interaction with the application, privacy measures, an

Author

gowrijaswanth31

Language

EN