A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.

The Qualcomm® AI Hub Models are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.

基于react和antd开发的cron表达式生成组件 React and Antd based cron expression generation components

Mobilenet v1 trained on Imagenet for STM32 using extended CMSIS-NN with INT-Q quantization support

Simplified AI runtime integration for mobile app development

The Qualcomm® AI Hub apps are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.

A Toolbox for Binarized Spectral Compressive Imaging (NeurIPS 2023)

This repository containts the pytorch scripts to train mixed-precision networks for microcontroller deployment, based on the memory contraints of the target device.

Kotlin bindings for Edgerunner

Low-Precision YOLO on PYNQ with FINN

INT-Q Extension of the CMSIS-NN library for ARM Cortex-M target

Official PyTorch repository for Quaternion Generative Adversarial Networks.

javascript literal object manipulation plug-in in code file | 代码文件中的js字面量对象操作插件

Scalable Quantum Neural Network builds and trains a large-scale QNN in a modular fashion. SQNN is evaluated with a binary classification task on the MNIST dataset.

The repository supports TensorRT, QNN platform inference, 2D obstacle detection yolo series (yolov5-yolo11), 3D obstacle detection BEV series (CNN & Transformer), semantic segmentation and so on.

In this repository, I classify the Iris dataset using Qutrits and IBM Quantum pulse technology.

Hybrid Quantum Neural Network for classification of the MNIST Dataset using Classiq

Feed forward QNN

QNN-based correlation for frictional pressure drop of non-azeotropic mixtures during cryogenic forced boiling.

Testing and playing around with QNNs using the mnist dataset