Traffic Sign ClassifierUdacity Self-Driving Car Engineer Nanodegree. Project: Build a Traffic Sign Recognition Classifier
Stars: ✭ 12 (-92.21%)
GtsrbConvolutional Neural Network for German Traffic Sign Recognition Benchmark
Stars: ✭ 65 (-57.79%)
Cat Dog Cnn ClassifierThis classifier use Convolution Neural Network approch for kaggle problem to classify Cat vs Dog images.
Stars: ✭ 19 (-87.66%)
Sigver wiwdLearned representation for Offline Handwritten Signature Verification. Models and code to extract features from signature images.
Stars: ✭ 112 (-27.27%)
Caffenet BenchmarkEvaluation of the CNN design choices performance on ImageNet-2012.
Stars: ✭ 700 (+354.55%)
Image classifierCNN image classifier implemented in Keras Notebook 🖼️.
Stars: ✭ 139 (-9.74%)
Plaquebox PaperRepo for Tang et al, bioRxiv 454793 (2018)
Stars: ✭ 23 (-85.06%)
Deep Visual Attention PredictionKeras implementation of paper 'Deep Visual Attention Prediction' which predicts human eye fixation on view-free scenes.
Stars: ✭ 19 (-87.66%)
YannThis toolbox is support material for the book on CNN (http://www.convolution.network).
Stars: ✭ 41 (-73.38%)
Computervision RecipesBest Practices, code samples, and documentation for Computer Vision.
Stars: ✭ 8,214 (+5233.77%)
Cnn graphConvolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Stars: ✭ 1,110 (+620.78%)
Brain Tumor Segmentation KerasKeras implementation of the multi-channel cascaded architecture introduced in the paper "Brain Tumor Segmentation with Deep Neural Networks"
Stars: ✭ 20 (-87.01%)
SaliencyTensorFlow implementation for SmoothGrad, Grad-CAM, Guided backprop, Integrated Gradients and other saliency techniques
Stars: ✭ 648 (+320.78%)
Image Caption Generator[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
Stars: ✭ 141 (-8.44%)
Tensorflow 101TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow
Stars: ✭ 642 (+316.88%)
Build OcrBuild an OCR for iOS apps
Stars: ✭ 17 (-88.96%)
Mtcnn PytorchJoint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
Stars: ✭ 531 (+244.81%)
All Classifiers 2019A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.
Stars: ✭ 22 (-85.71%)
FssgiExploratory Project on Fast Screen Space Global Illumination
Stars: ✭ 22 (-85.71%)
Dl Workshop SeriesMaterial used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
Stars: ✭ 857 (+456.49%)
Music recommenderMusic recommender using deep learning with Keras and TensorFlow
Stars: ✭ 528 (+242.86%)
Teacher Student TrainingThis 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.
Stars: ✭ 34 (-77.92%)
Keras Faster RcnnFaster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Stars: ✭ 28 (-81.82%)
Svhn CnnGoogle Street View House Number(SVHN) Dataset, and classifying them through CNN
Stars: ✭ 44 (-71.43%)
Keras model compressionModel Compression Based on Geoffery Hinton's Logit Regression Method in Keras applied to MNIST 16x compression over 0.95 percent accuracy.An Implementation of "Distilling the Knowledge in a Neural Network - Geoffery Hinton et. al"
Stars: ✭ 59 (-61.69%)
Convisualize nbVisualisations for Convolutional Neural Networks in Pytorch
Stars: ✭ 57 (-62.99%)
Tensorflow BookAccompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Stars: ✭ 4,448 (+2788.31%)
Age Gender EstimationKeras implementation of a CNN network for age and gender estimation
Stars: ✭ 1,195 (+675.97%)
Cnn Interpretability🏥 Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer’s Disease
Stars: ✭ 68 (-55.84%)
Sigmoidal aiTutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal
Stars: ✭ 103 (-33.12%)
Cs231n Convolutional Neural Networks SolutionsAssignment solutions for the CS231n course taught by Stanford on visual recognition. Spring 2017 solutions are for both deep learning frameworks: TensorFlow and PyTorch.
Stars: ✭ 110 (-28.57%)
Equivariant Transformers Equivariant Transformer (ET) layers are image-to-image mappings that incorporate prior knowledge on invariances with respect to continuous transformations groups (ICML 2019). Paper: https://arxiv.org/abs/1901.11399
Stars: ✭ 68 (-55.84%)
SimpsonrecognitionDetect and recognize The Simpsons characters using Keras and Faster R-CNN
Stars: ✭ 131 (-14.94%)
Pytorch Dc TtsText to Speech with PyTorch (English and Mongolian)
Stars: ✭ 122 (-20.78%)
Deep SteganographyHiding Images within other images using Deep Learning
Stars: ✭ 136 (-11.69%)
Food Recipe Cnnfood image to recipe with deep convolutional neural networks.
Stars: ✭ 448 (+190.91%)
PbaEfficient Learning of Augmentation Policy Schedules
Stars: ✭ 461 (+199.35%)
Practical Machine Learning With PythonMaster the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Stars: ✭ 1,868 (+1112.99%)
TfvosSemi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.
Stars: ✭ 151 (-1.95%)