Popular GitHub Repositories for Typical Periods

? The Speaker Recognition System consists of two phases, Feature Extraction and Recognition. ? In the Extraction phase, the Speaker's voice is recorded and typical number of features are extracted to form a model. ? During the Recognition phase, a speech sample is compared against a previously created voice print stored in the database. ? The highlight of the system is that it can identify the Speaker's voice in a Multi-Speaker Environment too. Multi-layer Perceptron (MLP) Neural Network based on error back propagation training algorithm was used to train and test the system. ? The system response time was 74 μs with an average efficiency of 95%.

Typical RAG implementation using Semantic Kernel, Semantic Memory and Aspire

City-GAN is a Generative Adversarial Neural Network that generates typical facades of various cities around the world.

The Covid-19-QBox-Chatbot Model is free pre-compiled chatbot model that addresses typical questions about the COVID-19 virus to help you handle high volumes of questions from your customers, partners and staff. You simply add it to your current chatbot training data.

Bot that addresses typical questions about the COVID-19 virus to help you handle high volumes of questions from your customers, partners and staff.

A low-code platform to execute a typical pipeline for machine learning tasks through quantum computers

Typical NLP projects for beginners

This repo to establishes (AIPRL-LIR) framework for Large Language Model overall evaluation and analysis through systematic monthly intelligence reports. Unlike typical AI research papers or commercial reports. It provides structured insights into AI model performance, benchmarking methodologies, Multi-hosting provider analysis, industry trends ....

This is a project that I worked on with my colleagues in the 6th Semester of my B.tech. In this project, we present a fully automatic method for skin lesion segmentation by leveraging UNet and FCN that is trained end to-end. For Skin lesion disease classification, we use a customized convolutional neural net. Designing a novel loss function based on Jaccard distance to eliminate the need of sample re-weighting, a typical procedure when using cross entropy as the loss function for image segmentation due to the strong imbalance between the number of foreground and background pixels.  Evaluated the effectiveness, efficiency, as well as generalization capability of the proposed framework on publicly available PH2 database and HAM10000 dataset.

? AI-Powered Healthcare for Underserved Communities | Android app with symptom analysis, periods and ovulation tracker, medication reminders, health education & emergency guidance | Built with Jetpack Compose & Google Gemini API | Open-Source

An intelligent, autonomous edge application that addresses issues of bandwidth, data privacy and latency in comparison to typical IoT solutions. This includes processing AI on edge devices using real-time services in a distributed manner, as opposed to cloud-based models.

Notebooks and utils for typical llm engineering tasks

YoloLint is a tool for automatic validation of dataset structure, annotation files, and image sizes in YOLO projects. It helps you catch typical errors in directory structure, YAML files, annotation files, and now also ensures all your images have the correct size before you start model training.

An app that visualizes up to four channels of fiberphotometry signals, lets you annotate events or periods, and provides statistical analyses on those events or periods.

A modern web application that lets you chat with AI-powered personas based on Twitter/X personalities. The AI will respond in the style and character of the selected personality, using their typical phrases, topics, and mannerisms.

An app that visualizes up to four channels of fiberphotometry signals, lets you annotate events or periods, and provides statistical analyses on those events or periods.

Replication package for PROBE-SWE: a dynamic benchmark to generate, validate, and analyze data-induced cognitive biases in GPAI on typical software-engineering dilemmas.

Simple implementation of a game tree structure in Java alongside some typical AI algorithms i.e. minimax with alpha-beta pruning and MCTS

A simple yet effective chatbot built using LangGraph and OpenAI, designed to handle context-aware conversations by leveraging the full message history. This project showcases a structured, modular approach to chatbot development, moving beyond the typical infinite-loop implementations.

Chat bot with vision, sound output and input, your typical AI Babe