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Real-time low light video enhancement using Neural Networks on mobile
Ayaan
In this blog post, we explore a neural network based solution for improving low light video and optimizing for mobile.
September 10, 2024
High efficiency ML-based embedded computer vision
Sandeep Mistry
Demonstrating the performance benefits of the NPU by running two TinyML applications on a modern microcontroller that is equipped with an Arm Ethos-U55 NPU.
July 25, 2024
AI for Bears Challenge: Empowering developers while fostering conservation
Ed Miller
Developing AI applications for camera trap data to non-invasively monitor bears and other wildlife.
July 22, 2024
On-device speaker identification for Digital Television (DTV)
Marcus Corbin
This blog post shows the results of a research project into speaker identification using a DNN. Learn more about the key performance results, and future applications in AI tasks.
July 11, 2024
Announcing Arm KleidiCV 0.1: Unleashing the power of Arm CPUs for image processing
Michael Platings
Learn about Arm KleidiCV, an open-source library of optimized routines for accelerating Computer Vision (CV) workloads on Arm CPUs. It is easily integrated into Any CV framework.
June 3, 2024
Arm KleidiAI: Helping AI frameworks elevate their performance on Arm CPUs
Gian Marco Iodice
Learn all about Arm KleidiAI, an open-source library for accelerating AI performance on any AI framework. KleidiAI is designed for easily integrating optimized routines for Arm CPUs.
June 3, 2024
Generative AI on mobile is running on the Arm CPU: here’s how
Gian Marco Iodice
Large Language Models (LLMs), a form of generative AI inference, can now run on the majority of mobile devices built on the Arm CPU. This blog explains how and why.
January 17, 2024
Take your neural networks to the next level with Arm's Machine Learning Inference Advisor
Annie Tallund
Calling all developers who want to maximize their neural network performance! We present the Arm MLIA, the work leading up to it and why it matters.
November 23, 2023
Optimizing AI models for Arm Ethos-U NPUs using the NVIDIA TAO Toolkit
Amogh Dabholkar
How developers can optimize their AI models for Arm Ethos-U NPUs using the NVIDIA TAO Toolkit.
October 20, 2023
ExecuTorch and TOSA enabling PyTorch on Arm platforms
Robert Elliott
Arm has worked with Meta to introduce support for Arm platforms in ExecuTorch.
October 17, 2023
Neural Network Model quantization on mobile
Roberto Lopez Mendez
Current state of quantization on mobile (Android) is presented. Post-Training Quantization and Quantization Aware Training (QAT) in TFLite are discussed.
October 17, 2023
Reviewing different Neural Network Models for Multi-Agent games on Arm using Unity
Sofia Jegnell
During the Game Developer Conference (GDC) in March 2023, we showcased our multi-agent demo called Candy Clash, which is a mobile game containing 100 intelligent agents.
September 11, 2023
Part 1: Build dynamic and engaging mobile games with multi-agent reinforcement learning
Koki Mitsunami
Using the Unity ML-Agents Toolkit, we developed Candy Clash demo, the multi-agent system, where dozens of rabbit characters work as a team, aiming to crack their opponent's egg.
August 16, 2023
Benefit of pruning and clustering a neural network for before deploying on Arm Ethos-U NPU
George Gekov
How to design a neural network so that the compiler is able to efficiently compress the weights of your ML model and benefit fully from the capabilities of the Ethos-U hardware?
July 22, 2023
Part 3: Build dynamic and engaging mobile games with multi-agent reinforcement learning
Koki Mitsunami
Using the Unity ML-Agents Toolkit, we developed Candy Clash demo, the multi-agent system, where dozens of rabbit characters work as a team, aiming to crack their opponent's egg.
July 3, 2023
Part 2: Build dynamic and engaging mobile games with multi-agent reinforcement learning
Koki Mitsunami
Using the Unity ML-Agents Toolkit, we developed Candy Clash demo, the multi-agent system, where dozens of rabbit characters work as a team, aiming to crack their opponent's egg.
June 28, 2023
Analyzing Machine Learning models on a layer-by-layer basis
George Gekov
In this blog, we demonstrate how to analyze a Machine Learning model on a layer-by-layer basis.
October 31, 2022
How audio development platforms can take advantage of accelerated ML processing
Mary Bennion
Join DSP Concepts and Alif Semiconductor at Arm DevSummit 2022 to discuss ML techniques commonly used for audio. Discover the features and benefits of the Audio Weaver platform.
October 24, 2022
How to Deploy PaddlePaddle on Arm Cortex-M with Arm Virtual Hardware
Liliya Wu
This blog introduces how to deploy a PP-OCRv3 English text recognition model on Arm Cortex-M55 processor with Arm Virtual Hardware.
August 31, 2022
Usability, performance, and new technologies for Machine Learning: Arm NN in 2021
James Conroy
In this blog post, read about advancements in ML with Arm NN 2021.
February 2, 2022
Vela Compiler: The first step to deploy your NN model on the Arm Ethos-U microNPU
Liliya Wu
As first step to deploy your NN model on Ethos-U, Vela Compiler is open-source and easy-use. Try it out and embrace the improvement of ML ability brought by Ethos-U to embedded system.
January 17, 2022
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