Pytorch implementation of network design paradigm described in the paper "Designing Network Design Spaces"
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Updated
Jul 25, 2024 - Python
Pytorch implementation of network design paradigm described in the paper "Designing Network Design Spaces"
In this project, we proposed a straightforward strategy to engineer Residual networks with fewer than 5M parameters for CIFAR10 dataset
Music genre classification project as part of the Numerical Analysis for Machine Learning course at Politecnico di Milano, A.Y 2022-2023.
ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry
KL severity grading using SE-ResNet and SE-DenseNet architectures trained with Cross Entropy loss and Focal Loss. The hyperparameters of focal loss have been fine-tuned as well. Further, Grad-CAM has been implemented for visualization purposes.
Official code for ResUNetplusplus for medical image segmentation (TensorFlow & Pytorch implementation)
Official implementation of NanoNet: Real-time medical Image segmentation architecture (IEEE CBMS)
I am aiming to write different Semantic Segmentation models from scratch with different pretrained backbones.
Poly-Attention Intel Transfer Segmentation Network for skin lesion segmentation
PyTorch Implementation of ResUnet++
This repository contains the original implementation of "iResSENet: An Accurate Convolutional Neural Network for Retinal Blood Vessel Segmentation".
Implementation of different attention mechanisms in TensorFlow and PyTorch.
Deep Learning studies.
GAiA is a UCI chess engine built with C++ 17, ONNX and Pytorch. It performs an in-depth analysis and uses a complex squeeze-and-excitation residual network to evaluate each chess board.
Official Pytorch implementation of the paper "Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification" (NeurIPS 2022)
A module for creating 3D ResNets with different depths and additional features.
Classification models trained on ImageNet. Keras.
The 'Advanced topics in Computer Science' big project by Duc Tran Van, Manh Hoang Duc, Hoang Pham Tuan Nguyen, Thang Pham Duc
Application of a self-normalizing network for object segmentation.
A collection of deep learning models (PyTorch implemtation)
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