Wide Residual Networks implemented in TensorLayer and TensorFlow.
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Updated
Oct 30, 2016 - Python
Wide Residual Networks implemented in TensorLayer and TensorFlow.
links of my implementation
Caffe Wide-Residual-Network (WRN) Generator
Minimalist Keras implementation for performing object recognition with deep learning
Residual Network of Residual Networks in Keras
Image classification using ResNet50. Image input from webcam.
Caffe implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915).
The implementation of ResNet using Tensorflow. This implementation is based on this paper: https://arxiv.org/pdf/1603.05027.pdf
ResNet for Cifar10
Anomaly Detection Discriminative GAN (ADD-GAN)
Python implementation of "Deep Residual Learning for Image Recognition" (http://arxiv.org/abs/1512.03385 - MSRA, winner team of the 2015 ILSVRC and COCO challenges).
Torch implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915).
Download the dataset from here: https://www.kaggle.com/alexattia/the-simpsons-characters-dataset/data
A simple app that predicts which Simpson character you make it see! Here is an example of it in action:
Employ SSD and RetinaNet for Standard Panel Detecion in US Image
A Deep Residual Convolutional Neural Network as Gender Classifier on an Interactive Webserver
Implementation of a Wide Residual Network on Tensorflow for Image Classification. Trained and tested on Cifar10 dataset.
A tutorial on Residual Networks which was originally proposed by Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun from Microsoft Research Team.
PyTorch implementation of residual networks trained on CIFAR-10 dataset (2017)
Decathlon Multiple Visual Domains with Residual Adapters in Keras
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