Maid is a cross-platform Flutter app for interfacing with GGUF / llama.cpp models locally, and with Ollama and OpenAI models remotely.
Embedded and mobile deep learning research resources
AI Image Signal Processing and Computational Photography. Official library for NTIRE (CVPR) and AIM (ICCV/ECCV) Challenges. You will find Learned ISPs, RAW Restoration-Upsampling-Reconstruction, Image Enhancement, Bokeh rendering and more!
Run large language models like Qwen and LLaMA locally on Android for offline, private, real-time question answering and chat - powered by ONNX Runtime.
MineGPT 是一个基于Kotlin Multiplatform 开发的本地小型语言模型(SLM)对话应用; MineGPT is a lightweight local SLM (Small Language Model) chat application built with Kotlin Multiplatform. It aims to provide a cross-platform and user-friendly AI assistant experience.
SharpAPI.com - Automate with AI-powered API. Leverage AI API for workflows automation in E-Commerce, Marketing, Content Management, HR Tech, Travel, and more.
Enhance your iOS app with the ability to see and interact with humans using the RGB camera.
[CVPRW 2025] Official repository of DTTDNet: Robust Digital-Twin Localization via An RGBD-based Transformer Network and A Comprehensive Evaluation on a Mobile Dataset
🚗 Driver Drowsiness Detection with Deep Learning (PoC) 🧠 A personal experiment comparing CNN + MobileNetV2 and YOLOv11 for real-time drowsiness detection. Focused on evaluating accuracy and efficiency to explore AI’s potential in preventing fatigue-related accidents. 😴⚡ A hands-on dive into safety-driven computer vision.
Review papers about neural networks for mobile devices
Measure the speed of your machine learning models on real devices!
An AI chatbot like ChatGPT & Gemini, powered by Google AI API 🌟🤖.
Protect your Machine Learning model in your Flutter application.
Edge device object detection with Kotlin & TensorFlow Lite Mobile & edge AI object detection using Kotlin
Create amazing food log reels and shorts
OnLLM is the platform to run LLM or SLM models using OnnxRuntime directly on low-end devices like low power computers, mobile phones etc. It is cross-platform using Kivy & open-source.
This repository serves as a showcase of multiple deep learning projects across domains like healthcare, customer analytics, and computer vision. Each project is implemented in Python using TensorFlow/Keras and is structured in Jupyter Notebooks for reproducibility and learning.
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