MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks. In NeurIPS 2020 workshop.
翻译 - 餐点V2：在没有技巧的情况下将ImageNet上的Vanilla ResNet-50提高到80％+ Top-1准确性
This implements training of popular model architectures, such as AlexNet, ResNet and VGG on the ImageNet dataset(Now we supported alexnet, vgg, resnet, squeezenet, densenet)
#计算机科学#Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning)
VGG16 Net implementation from PyTorch Examples scripts for ImageNet dataset
deeplearning.ai Tensorflow advance techniques specialization
CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders
ElasticModels is a elasticsearch object modeling tool designed to work in and asynchronous environment. Builded for official elasticsearch client library Main inspiration was mongoose project
#计算机科学#This Repository contains TensorFlow implementation of different Image Segmentation Architecture on different types of datasets.
#计算机科学#Automated Tool for Hierarchical Exploration of Neural Architectures
Official PyTorch and CVXPY implementation of Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming
#计算机科学#Identify traffic sign images through Supervised Classification via Deep Learning and Computer Vision using Python, Tensorflow, Jupyter and Anaconda in AWS Cloud.
#计算机科学#In this project I have designed a Traffic Sign Classifier, which classifies German Traffic Signs.
Building a network to predict steering angles from images
CNN model architecture implementations in Keras
Research project on trafiic sign recognition using deep learning and computer vision.
This is my first personal project about training a deep learning algorithm for road traffic signs recognition.
#计算机科学#Deep Learning Project to Teach a Car to Drive Autonomously Using Only Camera Images.