November 25, 2021 PyTorch

Sharpness-aware Quantization for Deep Neural Networks

This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Networks by Jing Liu, Jianfei Cai, and Bohan Zhuang. Recent Update 2021.11.24: We release the source code of SAQ. Setup the environments Clone the repository locally: git clone https://github.com/zhuang-group/SAQ Install pytorch 1.8+, tensorboard and prettytable conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch pip install tensorboard pip install prettytable Data preparation

November 25, 2021 Challenge

L3DAS22 challenge supporting API

This repository supports the L3DAS22 IEEE ICASSP Grand Challenge and it is aimed at downloading the dataset, pre-processing the sound files and the metadata, training and evaluating the baseline models and validating the final results.We provide easy-to-use instruction to produce the results included in our paper.Moreover, we extensively commented our code for easy customization. For further information please refer to the challenge website and to the challenge documentation. Installation Our code is based on Python 3.7. To install all required […]

November 25, 2021 Document

PhD document for navlab

The project contains the relative software documents which I developped or used during my PhD period. It includes: FLVIS. A stereo-inertial pose estimation system. RW_SLAM. A tightly-coupled system fusing RGB-D camera and wheel odometer. ESKF. An ESKF algorithm to fuse IMU and GNSS data. 3D reconstruction demo based on pcl and Open3D. Qualisys manual. The steps to set the IP of qualisys, calibrate and define a body frame, and get the groudtruth using ROS. Evaluation tools. The usages of EVO […]

November 25, 2021 augmentation

MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets)

MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets) Using mixup data augmentation as reguliraztion and tuning the hyper parameters of ResNet 50 models to achieve 94.57% test accuracy on CIFAR-10 Dataset. Link to paper network error % resnet-50 6.97 resnet-110 6.61 resnet-164 5.93 resnet-1001 7.61 This method 5.43 Overview Change the wandb api key to valid api key. Python 3.8 and pytorch 1.9 (works on older versions as well) main.py is to train model sweep.py and sweep_config.py are for […]

November 25, 2021 Simulation

HSPICE can not perform Monte Carlo (MC) simulations while considering aging effects

HSPICE can not perform Monte Carlo (MC) simulations while considering aging effects. I developed a python wrapper that automatically performs MC and aging simulations using HPSICE to save engineering hours. windows or linux python3 hspice Step1: Parses the spice file and reads the distribution and monte parameters Removes the distribution and monte parameters For example if monte parameter was 10, it creates 10 versions of the given spice filebut with width and length values changed according to the distributions it […]

November 25, 2021 Attack

Attack SQL Server through gopher protocol

usage: main.py [-h] –username USERNAME –password PASSWORD –database DATABASE –query QUERY Attack SQL Server through gopher protocol optional arguments: -h, –help show this help message and exit –username USERNAME, -u USERNAME mssql username –password PASSWORD, -p PASSWORD mssql password –database DATABASE, -d DATABASE mssql database name –query QUERY, -q QUERY mssql sql query statement

November 25, 2021 Kubernetes

Blazingly-fast , rock-solid, local application development with Kubernetes

Gefyra gives Kubernetes-(“cloud-native”)-developers a completely new way of writing and testing their applications.Over are the times of custom Docker-compose setups, Vagrants, custom scrips or other scenarios in order to develop (micro-)servicesfor Kubernetes. Gefyra offers you to: run services locally on a developer machine operate feature-branches in production-like Kubernetes environment with all adjacent services write code in the IDE you already love, be fast, be confident leverage all the neat development features, such as debugger, code-hot-reloading, override environment variables run high-level […]

November 24, 2021 Evaluation

Quick WAF paranoid Doctor Evaluation

WAFPARAN01D3 The Web Application Firewall Paranoia Level Test Tool. — From alt3kx.github.io Introduction to Paranoia Levels In essence, the Paranoia Level (PL) allows you to define how aggressive the Core Rule Set is. Reference: https://coreruleset.org/20211028/working-with-paranoia-levels/ How it works The wafparan01d3.py python3 script takes malicious requests using encoded payloads placed in different parts of HTTP requests based on GET parameters, The results of the evaluation are recorded in the report debug file wafparan01d3.log created on your machine. Observe the behavior and […]

November 24, 2021 Time

It’s About Time: Analog clock Reading in the Wild

Code repository for “It’s About Time: Analog clock Reading in the Wild” Packages required:pytorch (used 1.9, any reasonable version should work), kornia (for homography), einops, scikit-learn (for RANSAC), tensorboardX (for logging) Using pretrained model: prediction python predict.py will predict on your data (or by default, whatever is in data/demo). This does assume the images being already cropped, we use CBNetv2. (you could instead add something like a yolov5 to the code if you prefer not installing anything extra). evaluation python […]

November 24, 2021 Attention

ProtoAttend: Attention-Based Prototypical Learning

Authors: Sercan O. Arik and Tomas Pfister Paper: Sercan O. Arik and Tomas Pfister, “ProtoAttend: Attention-Based Prototypical Learning”Link: https://arxiv.org/abs/1902.06292 We propose a novel inherently interpretable machine learning method that bases decisions on few relevant examples that we call prototypes. Our method, ProtoAttend, can be integrated into a wide range of neural network architectures including pre-trained models. It utilizes an attention mechanism that relates the encoded representations to samples in order to determine prototypes. The resulting model outperforms state of the […]

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