Train and test Mask R-CNN and Sparse R-CNN on VOC dataset using mmdetection.
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Updated
May 29, 2025 - Python
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sparse-rcnn
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A comprehensive collection of implementations for Deep Neural Networks, including Autoencoders, MLPs, CNNs, RNNs (LSTM/GRU), Sparse R-CNN, Transformers, DCGAN, BEGAN, and WGAN-GP. Features applications in dimensionality reduction, face recognition with Angular Margin Loss, sentiment analysis, object detection, and NLP classification
nlp deep-learning sentiment-analysis transformers cnn pytorch lstm gru dcgan neural-networks rnn face-recognition object-detection autoencoders bert began wgan-gp self-attention angular-margin-loss sparse-rcnn
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Updated
Aug 26, 2026 - Jupyter Notebook
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