Sep 4, 2023 · Title:On the fly Deep Neural Network Optimization Control for Low-Power Computer Vision. Authors:Ishmeet Kaur, Adwaita Janardhan Jadhav. View ...
On the fly Deep Neural Network Optimization Control for Low-Power ...
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This paper presents a novel technique to allow DNNs to adapt their accuracy and energy consumption during run-time, without the need for any re-training.
Sep 4, 2023 · Low-Power Object Counting with Hierarchical Neural Networks ... Deep Neural Networks (DNNs) can achieve state-of-the-art accuracy in many computer ...
Deep neural networks (DNNs) are a class of machine learning algorithms that can achieve high accuracy on many computer vision tasks [12, 13, 14] . DNNs use ...
Recent machine learning breakthroughs in computer vision and natural language processing were possible due to Deep Neural Networks (DNNs) learning capabilities.
Sep 4, 2023 · On the fly Deep Neural Network Optimization Control for Low-Power Computer Vision ; 22 December 2020 by Jonathan Ashbrock and Alexander Powell.
On the fly Deep Neural Network Optimization Control for Low-Power Computer Vision · Low-power object counting with hierarchical neural networks · Efficient ...
This paper describes a low-power technique for the object re-identification (reID) problem: matching a query image against a gallery of previously seen images.
This paper presents a novel technique to allow DNNs to adapt their accuracy and energy consumption during run-time, without the need for any re-training, ...
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Oct 15, 2020 · This architecture uses multiple smaller DNNs (called modules) to progressively classify images into groups of categories based on a novel visual similarity ...