Showing results for records Vector
GitHub Repo
https://github.com/std-microblock/telegram-database
std-microblock/telegram-database
A simple and fast chat records searching bot for Telegram. Supports OCR and sematic vector search.
GitHub Repo
https://github.com/adamgann/av-uwa
adamgann/av-uwa
Auxiliary-vector based short data record filtering for underwater acoustic communications
GitHub Repo
https://github.com/gayathri1462/Breast-Cancer-Detection-Web-App
gayathri1462/Breast-Cancer-Detection-Web-App
SVM (Support Vector Machines) is used to build and train a model using human cell records, and classify cells to predict whether the samples are benign or malignant and display output using Flask Application On Heroku
GitHub Repo
https://github.com/amandaghassaei/LaserCutRecord
amandaghassaei/LaserCutRecord
generate vector cutting paths from digital audio to make a working record
GitHub Repo
https://github.com/ClementGre/PDF4Teachers
ClementGre/PDF4Teachers
PDF editing software for teachers, focused on productivity. PDF4Teachers keeps recorded previous annotations, and offers features like marking scale, PDF conversion, vectorial drawing...
GitHub Repo
https://github.com/louisblankemeier/STARR-Labeler
louisblankemeier/STARR-Labeler
Package for generating feature vectors and outcome labels from electronic health records.
GitHub Repo
https://github.com/bevacqua/vectorcam
bevacqua/vectorcam
:movie_camera: Record gifs out of <svg> elements painlessly
GitHub Repo
https://github.com/parmacalcio1913/players-matcher
parmacalcio1913/players-matcher
A production-ready fuzzy matching framework for linking player records across multiple data providers using TF-IDF vectorization and bidirectional validation.
GitHub Repo
https://github.com/vintasoftware/entity-embed
vintasoftware/entity-embed
PyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.
GitHub Repo
https://github.com/Piyush-Bhardwaj/EEG-based-emotion-analysis-using-DEAP-dataset-for-Supervised-Machine-Learning