760 Open source projects that are alternatives of or similar to Lsuvinit

Evaluation of the CNN design choices performance on ImageNet-2012.

💻 Make machines learn so that you don't have to struggle to program them; The ultimate list

CORe50: a new Dataset and Benchmark for Continual Learning

This repository stores the files used for my summer internship's work on "teacher-student learning", an experimental method for training deep neural networks using a trained teacher model.

vehicle image retrieval using k CNNs ensemble method

Code and weights for local feature affine shape estimation paper "Repeatability Is Not Enough: Learning Discriminative Affine Regions via Discriminability"

Object classification with CIFAR-10 using transfer learning

Outdated, see new https://github.com/braindecode/braindecode

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

Repository has been moved: https://github.com/adobe/antialiased-cnns

real-time fire detection in video imagery using a convolutional neural network (deep learning) - from our ICIP 2018 paper (Dunnings / Breckon) + ICMLA 2019 paper (Samarth / Bhowmik / Breckon)

Using Tensorflow to classify the NIST Dataset 19 (Handwriting)

O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis

Supervised Semantics-preserving Deep Hashing (TPAMI18)

FeatherCNN is a high performance inference engine for convolutional neural networks.

Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.

This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"

Caffe implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network" (CVPR 2018)

A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.

Image Deblurring using Generative Adversarial Networks

Deep Object Tracking Implementation in Tensorflow for 'Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning(CVPR 2017)'

Implementation based on the paper Li et al., “A Convolutional Neural Network Cascade for Face Detection, ” 2015 CVPR

Naszilla is a Python library for neural architecture search (NAS)

CNN visualization tool in TensorFlow

Keras tutorial for beginners (using TF backend)

Image Captioning: Implementing the Neural Image Caption Generator with python

Convolutional Neural Network for German Traffic Sign Recognition Benchmark

Breast Cancer Classification using CNN and transfer learning

Software and pre-trained models for automatic photo quality enhancement using Deep Convolutional Networks

Cifar-10 CNN implementation using TensorFlow library with 20% error.

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

CVPR2014-Convolutional neural networks for no-reference image quality assessment

AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charitable hospitals, and organizations like WHO 🌏 We will also release our pretrained models and weights as Medical Imagenet.

Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data.

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

Pytorch implementation of ACCV18 paper "Revisiting Distillation and Incremental Classifier Learning."

A convolutional neural network for graph classification in PyTorch

Bayes by Backprop implemented in a CNN in PyTorch

Deep Learning in Haskell

Xilinx Deep Learning IP

MobileNet-SSD(MobileNetSSD) + Neural Compute Stick(NCS) Faster than YoloV2 + Explosion speed by RaspberryPi · Multiple moving object detection with high accuracy.

Generating Captions for images using Deep Learning

Biologically-realistic recurrent convolutional neural networks

Add-on package for ONNX format support in Chainer

Convolutional Neural Networks for Cardiac Segmentation

(This repo is no longer up-to-date. Any updates will be at https://github.com/DeepRegNet/DeepReg/) A demo of the re-factored label-driven registration code, based on "Weakly-supervised convolutional neural networks for multimodal image registration"

A MNIST-like fashion product database. Benchmark 👇

《深度学习与计算机视觉》配套代码

Convolutional Neural Networks to predict the aesthetic and technical quality of images.

Classify each facial image into one of the seven facial emotion categories considered using CNN based on https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras

A Computation Graph Virtual Machine Based Deep Learning Framework

Official Implementation of 'Fast AutoAugment' in PyTorch.

Recognizes the facial emotion and overlays emoji, equivalent to the emotion, on the persons face.

Unity Post Processing with Convolution Neural Network

R interface to the keras library

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape