418 skills found · Page 1 of 14
kerlomz / Captcha Trainer[验证码识别-训练] This project is based on CNN/ResNet/DenseNet+GRU/LSTM+CTC/CrossEntropy to realize verification code identification. This project is only for training the model.
pnnl / NeuromancerPytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
arx-deidentifier / ArxARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy.
google-research-datasets / PawsThis dataset contains 108,463 human-labeled and 656k noisily labeled pairs that feature the importance of modeling structure, context, and word order information for the problem of paraphrase identification.
wilsonrljr / SysidentpyA Python Package For System Identification Using NARMAX Models
Syliz517 / CLIP ReIDOfficial implementation for "CLIP-ReID: Exploiting Vision-Language Model for Image Re-identification without Concrete Text Labels" (AAAI 2023)
zeusees / HyperVID开源移动端车型识别 Mobile Plateform Vehicle Identification Model
a-nagrani / VGGVoxVGGVox models for Speaker Identification and Verification trained on the VoxCeleb (1 & 2) datasets
kitoweeknd / RFUAVThis is official repository of our paper "RFUAV: A Benchmark Dataset for Unmanned Aerial Vehicle Detection and Identification". Codes include a two stage model to achieve drone detection and classification using some FFT/STFT analytical method. The Raw data will be free to use after our paper is accept. Star us!!!!, if you think this is useful♥
nelson-liu / Paraphrase Id TensorflowVarious models and code (Manhattan LSTM, Siamese LSTM + Matching Layer, BiMPM) for the paraphrase identification task, specifically with the Quora Question Pairs dataset.
tugstugi / Pytorch SaltnetKaggle | 9th place single model solution for TGS Salt Identification Challenge
cdsousa / SymPyBotics[UNMAINTAINED] Symbolic Framework for Modeling and Identification of Robot Dynamics
arcee-ai / PruneMeAutomated Identification of Redundant Layer Blocks for Pruning in Large Language Models
SurajDonthi / Multi Camera Person Re IdentificationState-of-the-art model for person re-identification in Multi-camera Multi-Target Tracking. Benchmarked on Market-1501 and DukeMTMTC-reID datasets.
Nirvan101 / Person Re IdentificationDetection, tracking and re-identification of people in a surveillance video to make a list of people that appeared in the video. If people leave the frame and re-appear later in the video, the model recognizes them from before and does not count them multiple times.
gandalf1819 / Stock Market Sentiment AnalysisIdentification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka
hlamba28 / UNET TGSApplying UNET Model on TGS Salt Identification Challenge hosted on Kaggle
instadeepai / TunbertTunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset. TunBERT was applied to three NLP downstream tasks: Sentiment Analysis (SA), Tunisian Dialect Identification (TDI) and Reading Comprehension Question-Answering (RCQA)
lmcggg / Data Driven MPCA MATLAB implementation of Data-Driven Model Predictive Control (DDMPC) for linear time-invariant (LTI) systems that does not require explicit system identification.
EI-CoreBioinformatics / MikadoMikado is a lightweight Python3 pipeline whose purpose is to facilitate the identification of expressed loci from RNA-Seq data * and to select the best models in each locus.
