1158 Open source projects that are alternatives of or similar to Neural Backed Decision Trees

Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search

Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)

Sandbox for training deep learning networks

Easily train or fine-tune SOTA computer vision models with one open source training library

Implementation of EfficientNet model. Keras and TensorFlow Keras.

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PyTorch-based modular, configuration-driven framework for knowledge distillation. 🏆18 methods including SOTA are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy.

PiGallery: AI-powered Self-hosted Secure Multi-user Image Gallery and Detailed Image analysis using Machine Learning, EXIF Parsing and Geo Tagging

Bottleneck Transformers for Visual Recognition

Segmentation models with pretrained backbones. PyTorch.

Brevitas: quantization-aware training in PyTorch

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Labelbox is the fastest way to annotate data to build and ship computer vision applications.

Pytorch implementation of network design paradigm described in the paper "Designing Network Design Spaces"

implement AlexNet with C / convolutional nerual network / machine learning / computer vision

Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

RectLabel - An image annotation tool to label images for bounding box object detection and segmentation.

🐰 Python lib for remo - the app for annotations and images management in Computer Vision

Official Pytorch implementation of ReXNet (Rank eXpansion Network) with pretrained models

AutoML frAmework for Neural Networks

Deep learning codes and projects using Python

72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models

Parametric Contrastive Learning (ICCV2021)

73.6% GhostNet 1.0x pre-trained model on ImageNet

Deep Learning Computer Vision Algorithms for Real-World Use

[Paper 2020] Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training. Plus, an image classification toolbox includes ResNet, Wide-ResNet, ResNeXt, ResNeSt, ResNeXSt, SENet, Shake-Shake, DenseNet, PyramidNet, and EfficientNet.

A collection of computer vision pre-trained models.

Mobilenet V2(Inverted Residual) Implementation & Trained Weights Using Tensorflow

🍊 🎑 Orange3 add-on for dealing with image related tasks

Image Classification on CIFAR-10 Dataset using Multi Layer Perceptrons in Python from Scratch.

Etiketai is an online tool designed to label images, useful for training AI models

[IEEE Access] "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems" and [ACM MobiCom HotEdgeVideo 2019] "Distilled Split Deep Neural Networks for Edge-assisted Real-time Systems"

A collection of SOTA Image Classification Models in PyTorch

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

Implementation of Quickdraw - an online game developed by Google

Visualization toolkit for neural networks in PyTorch! Demo -->

MemeGen is a web application where the user gives an image as input and our tool generates a meme at one click for the user.

🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images

Various CNN models for CIFAR10 with Chainer

Train the HRNet model on ImageNet

Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification

PyTorch implementation of shake-drop regularization

No description or website provided.

Implementation of Conv-based and Vit-based networks designed for CIFAR.

Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.

74.3% MobileNetV3-Large and 67.2% MobileNetV3-Small model on ImageNet

Neural networks training pipeline based on PyTorch

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PyTorch-style and human-readable RegNet with a spectrum of pre-trained models

HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Programming Assignments and Lectures for Stanford's CS 231: Convolutional Neural Networks for Visual Recognition

Powerful and efficient Computer Vision Annotation Tool (CVAT)

Label Studio is a multi-type data labeling and annotation tool with standardized output format

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.

Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"

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