There are 1 repository under qnn topic.
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.
Mobilenet v1 trained on Imagenet for STM32 using extended CMSIS-NN with INT-Q quantization support
基于react和antd开发的cron表达式生成组件 React and Antd based cron expression generation components
Simplified AI runtime integration for mobile app development
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
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.
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.
In this repository, I classify the Iris dataset using Qutrits and IBM Quantum pulse technology.
Feed forward QNN
Hybrid Quantum Neural Network for classification of the MNIST Dataset using Classiq
QNN-based correlation for frictional pressure drop of non-azeotropic mixtures during cryogenic forced boiling.
Quantum Neural Network (QNN), Variational Quantum Eigensolver (VQE)
Diabetic Retinotherapy using Quantum Computing
Implementation of a Quantized Neural Network with low bitwidth of weights, activations and gradients.