27 Repositories
Python moon-phase Libraries
Official Implementation of CVPR 2022 paper: "Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning"
(CVPR 2022) Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning ArXiv This repo contains Official Implementat
Moon-TikTok-Checker - A TikTok Username checking tool that probably 3/4 people use to get rare usernames
Moon Checker (educational Purposes Only) What Is Moon Checker? This is a TikTok
Code for Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Under construction. Description Code for Phase diagram of S
ANN model for prediction a spatio-temporal distribution of supercooled liquid in mixed-phase clouds using Doppler cloud radar spectra.
VOODOO Revealing supercooled liquid beyond lidar attenuation Explore the docs » Report Bug · Request Feature Table of Contents About The Project Built
A Pose Estimator for Dense Reconstruction with the Structured Light Illumination Sensor
Phase-SLAM A Pose Estimator for Dense Reconstruction with the Structured Light Illumination Sensor This open source is written by MATLAB Run Mode Open
Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection
An official implementation of paper Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection
Implementation of Hire-MLP: Vision MLP via Hierarchical Rearrangement and An Image Patch is a Wave: Phase-Aware Vision MLP.
Hire-Wave-MLP.pytorch Implementation of Hire-MLP: Vision MLP via Hierarchical Rearrangement and An Image Patch is a Wave: Phase-Aware Vision MLP Resul
Simple proxy scraper made by using ProxyScrape's api.
What is Moon? Moon is a lightweight and fast proxy scraper made by using ProxyScrape's api. What can i do with this? You can use proxies for varietys
Python calculations for the position of the sun and moon.
Astral This is 'astral' a Python module which calculates Times for various positions of the sun: dawn, sunrise, solar noon, sunset, dusk, solar elevat
Moon-patrol - A faithful recreation of the 1983 hit classic Moon Patrol for the Atari 2600 created using the Pygame library for Python
Moon Patrol A recreation of the hit Atari 2600 game, Moon Patrol Moon Patrol is
ARRU seismic backprojection - Earthquake waveform detection and P/S arrivals picking on continuous data using ARRU phase picker
ARRU_seismic_backprojection Earthquake waveform detection and P/S arrivals picki
"Learning Free Gait Transition for Quadruped Robots vis Phase-Guided Controller"
PhaseGuidedControl The current version is developed based on the old version of RaiSim series, and possibly requires further modification. It will be
Modified prey-predator system - Modified prey–predator model describes the rate of change for each species by adding coupling terms.
Modified prey-predator system We aim to study the behaviors of the modified prey–predator model and establish the effects of several parameters that p
Chronocalc - Calculates the dates and times when the sun or moon is in a given position in the sky
Chronocalc I wrote this script after I was busy updating my article on chronoloc
Hydrogen (or other pure gas phase species) depressurization calculations
HydDown Hydrogen (or other pure gas phase species) depressurization calculations This code is published under an MIT license. Install as simple as: pi
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
PyTorch implementation of MICCAI 2018 paper "Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector"
Grouped SSD (GSSD) for liver lesion detection from multi-phase CT Note: the MICCAI 2018 paper only covers the multi-phase lesion detection part of thi
The code is the training example of AAAI2022 Security AI Challenger Program Phase 8: Data Centric Robot Learning on ML models.
Example code of [Tianchi AAAI2022 Security AI Challenger Program Phase 8]
Two phase pipeline + StreamlitTwo phase pipeline + Streamlit
Two phase pipeline + Streamlit This is an example project that demonstrates how to create a pipeline that consists of two phases of execution. In betw
The project of phase's key role in complex and real NN
Phase-in-NN This is the code for our project at Princeton (co-authors: Yuqi Nie, Hui Yuan). The paper title is: "Neural Network is heterogeneous: Phas
A Closer Look at Reference Learning for Fourier Phase Retrieval
A Closer Look at Reference Learning for Fourier Phase Retrieval This repository contains code for our NeurIPS 2021 Workshop on Deep Learning and Inver
QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place — so you can focus on building the next big thing.
QuakeLabeler Quake Labeler was born from the need for seismologists and developers who are not AI specialists to easily, quickly, and independently bu
[ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
Amplitude-Phase Recombination (ICCV'21) Official PyTorch implementation of "Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neur
object detection; robust detection; ACM MM21 grand challenge; Security AI Challenger Phase VII
赛题背景 在商品知识产权领域,知识产权体现为在线商品的设计和品牌。不幸的是,在每一天,存在着非法商户通过一些对抗手段干扰商标识别来逃避侵权,这带来了很高的知识产权风险和财务损失。为了促进先进的多媒体人工智能技术的发展,以保护企业来之不易的创作和想法免受恶意使用和剽窃,因此提出了鲁棒性标识检测挑战赛
Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)
Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)
NExT-QA: Next Phase of Question-Answering to Explaining Temporal Actions (CVPR2021)
NExT-QA We reproduce some SOTA VideoQA methods to provide benchmark results for our NExT-QA dataset accepted to CVPR2021 (with 1 'Strong Accept' and 2
One Stop Anomaly Shop: Anomaly detection using two-phase approach: (a) pre-labeling using statistics, Natural Language Processing and static rules; (b) anomaly scoring using supervised and unsupervised machine learning.
One Stop Anomaly Shop (OSAS) Quick start guide Step 1: Get/build the docker image Option 1: Use precompiled image (might not reflect latest changes):