Randwire tensorflowtensorflow implementation of Exploring Randomly Wired Neural Networks for Image Recognition
Stars: ✭ 29 (+70.59%)
Caffe ModelCaffe models (including classification, detection and segmentation) and deploy files for famouse networks
Stars: ✭ 1,258 (+7300%)
Resnet On Cifar10Reimplementation ResNet on cifar10 with caffe
Stars: ✭ 123 (+623.53%)
Caffe2 IosCaffe2 on iOS Real-time Demo. Test with Your Own Model and Photos.
Stars: ✭ 221 (+1200%)
cnn-rnn-classifierA practical example on how to combine both a CNN and a RNN to classify images.
Stars: ✭ 47 (+176.47%)
HateALERT-EVALITACode for replicating results of team 'hateminers' at EVALITA-2018 for AMI task
Stars: ✭ 13 (-23.53%)
scorubyRuby Scoring API for PMML
Stars: ✭ 69 (+305.88%)
MoeFlowRepository for anime characters recognition website, powered by TensorFlow
Stars: ✭ 113 (+564.71%)
dzetsakadzetsaka : classification plugin for Qgis
Stars: ✭ 61 (+258.82%)
ConformerOfficial code for Conformer: Local Features Coupling Global Representations for Visual Recognition
Stars: ✭ 345 (+1929.41%)
crowd density segmentationThe code for preparing the training data for crowd counting / segmentation algorithm.
Stars: ✭ 21 (+23.53%)
Skin-Cancer-SegmentationClassification and Segmentation with Mask-RCNN of Skin Cancer using ISIC dataset
Stars: ✭ 61 (+258.82%)
flexinferA flexible Python front-end inference SDK based on TensorRT
Stars: ✭ 83 (+388.24%)
SWCaffeA Deep Learning Framework customized for Sunway TaihuLight
Stars: ✭ 37 (+117.65%)
VideoAudit📹 一个短视频APP视频内容安全审核的思路调研及实现汇总
Stars: ✭ 221 (+1200%)
fooddistAn open-source food image embedding model
Stars: ✭ 26 (+52.94%)
numpy-cnnA numpy based CNN implementation for classifying images
Stars: ✭ 47 (+176.47%)
R-Machine-LearningD-Lab's 6 hour introduction to machine learning in R. Learn the fundamentals of machine learning, regression, and classification, using tidymodels in R.
Stars: ✭ 27 (+58.82%)
EC-GANEC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs (AAAI 2021)
Stars: ✭ 29 (+70.59%)
caffe-unet-dockerThe U-Net Segmentation server (caffe_unet) for Docker
Stars: ✭ 25 (+47.06%)
classySuper simple text classifier using Naive Bayes. Plug-and-play, no dependencies
Stars: ✭ 12 (-29.41%)
Deep-Learning-with-CaffeMy tests and experiments on Caffe, the deep learning framework by Berkeley Vision and Learning Center (BVLC) and its contributors.
Stars: ✭ 30 (+76.47%)
SGDLibraryMATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
Stars: ✭ 165 (+870.59%)
onnx2caffepytorch to caffe by onnx
Stars: ✭ 341 (+1905.88%)
embeddingsEmbeddings: State-of-the-art Text Representations for Natural Language Processing tasks, an initial version of library focus on the Polish Language
Stars: ✭ 27 (+58.82%)
textlearnRA simple collection of well working NLP models (Keras, H2O, StarSpace) tuned and benchmarked on a variety of datasets.
Stars: ✭ 16 (-5.88%)
colorchecker-detectionMultiple ColorChecker Detection. This code implements a multiple colorChecker detection method, as described in the paper Fast and Robust Multiple ColorChecker Detection.
Stars: ✭ 51 (+200%)
caffemodel2jsonA small tool to dump Caffe's *.caffemodel to JSON for inspection
Stars: ✭ 40 (+135.29%)
PCN-WindowsNo description or website provided.
Stars: ✭ 21 (+23.53%)
ck-crowd-scenariosPublic scenarios to crowdsource experiments (such as DNN crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework across diverse mobile devices provided by volunteers. Results are continuously aggregated at the open repository of knowledge:
Stars: ✭ 22 (+29.41%)
caffe-char-rnnMulti-layer Recurrent Neural Networks (with LSTM) for character-level language models in Caffe
Stars: ✭ 25 (+47.06%)
Caffe BEGANCaffe/C++ implementation of Boundary Equilibrium Generative Adversarial Networks paper for face generation
Stars: ✭ 22 (+29.41%)
BIRADS classifierHigh-resolution breast cancer screening with multi-view deep convolutional neural networks
Stars: ✭ 122 (+617.65%)
vitaVita - Genetic Programming Framework
Stars: ✭ 24 (+41.18%)
DCGAN-CIFAR10A implementation of DCGAN (Deep Convolutional Generative Adversarial Networks) for CIFAR10 image
Stars: ✭ 18 (+5.88%)
pcdarts-tf2PC-DARTS (PC-DARTS: Partial Channel Connections for Memory-Efficient Differentiable Architecture Search, published in ICLR 2020) implemented in Tensorflow 2.0+. This is an unofficial implementation.
Stars: ✭ 25 (+47.06%)
dehaze[Preprint] "Improved Techniques for Learning to Dehaze and Beyond: A Collective Study"
Stars: ✭ 46 (+170.59%)
fpga caffeNo description or website provided.
Stars: ✭ 116 (+582.35%)