Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
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Updated
Aug 21, 2024 - Python
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
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)
This code includes classification and detection tasks in Computer Vision, and semantic segmentation task will be added later.
⭐⭐⭐ 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
Abnormal Behavior Recognition
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)
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
Implementation of some basic Image Annotation methods (using various loss functions & threshold optimization) on Corel-5k dataset with PyTorch library
keras implementation of custom backbones
PyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).
Classification models trained on ImageNet. Keras.
tf-keras-implemented YOLOv2
Keras (Tensorflow) code for the manuscript 'DenseUNets with feedback non-local attention for the segmentation of specular images of the corneal endothelium with Fuchs dystrophy'
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