Mobile Ai
Showing 14 of 14 projects
A high-performance neural network inference framework optimized for mobile platforms, enabling efficient AI deployment on edge devices.
An abstraction layer over MetalPerformanceShaders for crafting and running fast neural networks on iOS using TensorFlow models.
An example Android project demonstrating how to build and integrate TensorFlow for object detection using the camera.
A curated collection of TensorFlow Lite models, sample apps, tools, and learning resources for mobile and edge AI development.
A lightweight encoder-decoder neural network for real-time semantic segmentation on resource-constrained devices.
Convert Torch7 neural network models to Apple CoreML format for deployment on iOS/macOS devices.
An iOS library that applies artistic styles to images using Core ML and pre-trained neural style transfer models.
A collection of iOS sample apps demonstrating Generative AI capabilities including OpenAI, local LLMs, Stable Diffusion, and speech recognition.
Android client library for integrating IBM Watson cognitive services like speech recognition, text-to-speech, and visual recognition.
A collection of refactored, high-quality Android examples demonstrating TensorFlow Lite for on-device machine learning tasks.
Capacitor plugin for running LLM models locally on iOS and Android, supporting Apple Intelligence and MediaPipe.
Sample code demonstrating Core ML integration with ResNet50 and custom models converted via coremltools.
A 3-layer neural network library for iOS implementing Back Propagation Neural Network (BPN) with QuickProp and Kecman's theory.
A React Native app using TensorFlow.js and MobileNet for real-time object detection on mobile devices.
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