This code includes classification and detection tasks in Computer Vision, and semantic segmentation task will be added later.
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Updated
May 7, 2024 - Python
This code includes classification and detection tasks in Computer Vision, and semantic segmentation task will be added later.
DeepFake Detection Web-App[Mirage Breaker] 🖥 using Deep Learning(ResNext and LSTM), Flask and ReactJs where you can predict whether a video is FAKE Or REAL along with the confidence ratio.
⭐⭐⭐ Pytorch implementation of Attentiom, Backbone, ViT, MLP, Re-parameter, Convolution, very flexible module combination.
Speech commands recognition with PyTorch | Kaggle 10th place solution in TensorFlow Speech Recognition Challenge
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Abnormal Behavior Recognition
A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
Training pipeline for alzheimers classification with custom built EfficientNet and ResNeXt models.
Boundary detection using Probability of Boundary || Implementation and analysis of deep learning architectures such as ResNet, DenseNet, etc.
Deployed web application for alzheimers classification using ResNeXt-50 built from scratch in PyTorch
Visual Question Answering in Persian Based on deep learning techniques (paper code)
Various CNN's trained with the Kaggle Chest X-Ray dataset.
Food detection and recommendation with deep learning
利用pytorch实现图像分类的一个完整的代码,训练,预测,TTA,模型融合,模型部署,cnn提取特征,svm或者随机森林等进行分类,模型蒸馏,一个完整的代码
Pytorch implementation of vision models.
Code for paper: "Improved Residual Network Based on Norm-Preservation for Visual Recognition" https://doi.org/10.1016/j.neunet.2022.10.023
This projects aims in detection of video deepfakes using deep learning techniques like ResNext and LSTM. We have achived deepfake detection by using transfer learning where the pretrained ResNext CNN is used to obtain a feature vector, further the LSTM layer is trained using the features.
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