Displaying 1 to 20 from 29 results

tf-faster-rcnn - Tensorflow Faster RCNN for Object Detection

  •    Python

For a good and more up-to-date implementation for faster/mask RCNN with multi-gpu support, please see the example in TensorPack here. A Tensorflow implementation of faster RCNN detection framework by Xinlei Chen (xinleic@cs.cmu.edu). This repository is based on the python Caffe implementation of faster RCNN available here.

mmclassification - OpenMMLab Image Classification Toolbox and Benchmark

  •    Jupyter

MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. This project is released under the Apache 2.0 license.

BMW-TensorFlow-Training-GUI - This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! NoCode training with TensorFlow has never been so easy

  •    Python

This repository allows you to get started with training a State-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset and you can start the training right away and monitor it with TensorBoard. You can even test your model with our built-in Inference REST API. Training with TensorFlow has never been so easy.




tensornets - High level network definitions with pre-trained weights in TensorFlow

  •    Python

High level network definitions with pre-trained weights in TensorFlow (tested with >= 1.1.0). You can install TensorNets from PyPI (pip install tensornets) or directly from GitHub (pip install git+https://github.com/taehoonlee/tensornets.git).

TF-Tutorials - A collection of deep learning tutorials using Tensorflow and Python

  •    Jupyter

#Tensorflow Tutorials This repository contains a collection of miscellaneous Jupyter notebooks which implement or provide a tutorial on a different Deep Learning topic. All models are implemented in Tesnorflow.

cnn-models - ImageNet pre-trained models with batch normalization for the Caffe framework

  •    Python

This repository contains convolutional neural network (CNN) models trained on ImageNet by Marcel Simon at the Computer Vision Group Jena (CVGJ) using the Caffe framework as published in the accompanying technical report. Each model is in a separate subfolder and contains everything needed to reproduce the results. This repository focuses currently contains the batch-normalization-variants of AlexNet and VGG19 as well as the training code for Residual Networks (Resnet). No mean subtraction is required for the pre-trained models! We have a batch-normalization layer which basically does the same.

awesome-very-deep-learning - 🔥A curated list of papers and code about very deep neural networks

  •    

awesome-very-deep-learning is a curated list for papers and code about implementing and training very deep neural networks. Value Iteration Networks are very deep networks that have tied weights and perform approximate value iteration. They are used as an internal (model-based) planning module.


self-label - Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)

  •    Python

🆕✅🎉 updated code: 23rd April 2020: bug fixes + CIFAR code + evaluation for resnet & alexnet. Checkout our blogpost for a quick non-technical overview and an interactive visualization of our clusters.

ResNeXt-DenseNet - PyTorch Implementation for ResNet, Pre-Activation ResNet, ResNeXt, DenseNet, and Group Normalisation

  •    Python

PyTorch Implementation for ResNet, Pre-Activation ResNet, ResNeXt, DenseNet, and Group Normalisation

pytorch-speech-commands - Speech commands recognition with PyTorch

  •    Python

Convolutional neural networks for Google speech commands data set with PyTorch. We, xuyuan and tugstugi, have participated in the Kaggle competition TensorFlow Speech Recognition Challenge and reached the 10-th place. This repository contains a simplified and cleaned up version of our team's code.

resnet.torch - an updated version of fb.resnet.torch with many changes.

  •    Jupyter

This is a fork of https://github.com/facebook/fb.resnet.torch. Refer to that if you need to know the details of this library. This code is heavily modified with many additions throughout my research. Many of the changes are optional and defined in "opts.lua". Here is the list of the additions by no means complete.

ResNeXt.pytorch - Reproduces ResNet-V3 with pytorch

  •    Python

Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch. It should reach ~3.65% on Cifar-10, and ~17.77% on Cifar-100.

tensorbag - Collection of tensorflow notebooks tutorials for implementing the most important Deep Learning algorithms

  •    Jupyter

Tensorbag is a collection of tensorflow tutorial on different Deep Learning and Machine Learning algorithms. The tutorials are organised as jupyter notebooks and require tensorflow >= 1.5. There is a subset of notebooks identified with the tag [quiz] that directly ask to the reader to complete part of the code. In the same folder there is always a complementary notebook with the complete solution.

SENet-Caffe - A Caffe Re-Implementation of SENet

  •    

For offical implementations, please check this repo SENet. Here we provide a pretrained SE-ResNet-50 model on ImageNet, which achieves slightly better accuracy rates than the original one reported in the official repo. You can use the official bvlc caffe to run this model without any modifications.

resnet-cifar10-caffe - ResNet 20 32 44 56 110 for CIFAR10 with caffe

  •    Python

seems there's no much difference between resnet-20 and plain-20. However, from the second plot, you can see that plain-110 have difficulty to converge.

Tensorflow-Computer-Vision-Tutorial - Tutorials of deep learning for computer vision.

  •    Python

In these tutorials, we will learn to build several Convolutional Neural Networks (CNNs) developed recent years. All methods mentioned below are working in progress. Later, they will have their video and text tutorial in Chinese. Visit 莫烦 Python for more.

ResNetCAM-keras - Keras implementation of a ResNet-CAM model

  •    Python

The original Matlab implementation and paper (for AlexNet, GoogLeNet, and VGG16) can be found here. A Keras implementation of VGG-CAM can be found here. This implementation is written in Keras and uses ResNet-50, which was not explored in the original paper.






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