MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks. In NeurIPS 2020 workshop.
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Updated
Dec 24, 2021 - Python
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks. In NeurIPS 2020 workshop.
This repository contains the source code of our work on designing efficient CNNs for computer vision
Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning)
ImageNet file xml format to Darknet text format
SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression
PyTorch Implementation of SOTA SSL methods
A PyTorch implementation of universal adversarial perturbation (UAP) which is more easy to understand and implement.
ImageNet-1K data download, processing for using as a dataset
Code for the paper "A Study of Face Obfuscation in ImageNet"
Object Detection for Video with MXNet and GluonCV using YOLOv3
A Distributed ResNet on multi-machines each with one GPU card.
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
"Exploring Simple Siamese Representation Learning" PyTorch implementation
Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curve.
Creates subsets of ImageNet (e.g. ImageNet100)
Tensorflow Faster R-CNN for Windows and Python 3.5
[TPAMI-22] Bottom-up, voting based video object detection method
Artificial Intelligence in Assistive Technology. Using AI and Machine Learning we can redefine what vision means for visually impaired or blind.
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