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Image Quality AssessmentConvolutional Neural Networks to predict the aesthetic and technical quality of images.
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Pyseetapython api for SeetaFaceEngine(https://github.com/seetaface/SeetaFaceEngine.git)
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TnnBiologically-realistic recurrent convolutional neural networks
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LsuvinitReference caffe implementation of LSUV initialization
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Har Keras CnnHuman Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras
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Pynq DlXilinx Deep Learning IP
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GrenadeDeep Learning in Haskell
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InsightfaceState-of-the-art 2D and 3D Face Analysis Project
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DpedSoftware and pre-trained models for automatic photo quality enhancement using Deep Convolutional Networks
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Fast AutoaugmentOfficial Implementation of 'Fast AutoAugment' in PyTorch.
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Idn CaffeCaffe implementation of "Fast and Accurate Single Image Super-Resolution via Information Distillation Network" (CVPR 2018)
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Tensorflow Cifar 10Cifar-10 CNN implementation using TensorFlow library with 20% error.
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ExermoteUsing Machine Learning to predict the type of exercise from movement data
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CnniqaCVPR2014-Convolutional neural networks for no-reference image quality assessment
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Fashion MnistA MNIST-like fashion product database. Benchmark 👇
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Facial Expression RecognitionClassify 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
Stars: ✭ 82 (-24.77%)
Mp Cnn TorchMulti-Perspective Convolutional Neural Networks for modeling textual similarity (He et al., EMNLP 2015)
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EmnistA project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.
Stars: ✭ 81 (-25.69%)
ProjectaiaiAiAi.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.
Stars: ✭ 92 (-15.6%)
GhostnetCV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.
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YnetY-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images
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