Enhancing Deep Learning Sustainability by Synchronized Multi Augmentation with Rotations and Multi-Backbone Architectures

Enhancing Deep Learning Sustainability by Synchronized Multi Augmentation with Rotations and Multi-Backbone Architectures

Deep learning applications for Edge Intelligence (EI) face challenges in achieving high model performance while maintaining computational efficiency, particularly under varying image orientations and perspectives. This study investigates the synergy of multi-backbone (MB) configurations and Synchron...

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Bibliographic Details
Main Authors: Nikita Gordienko, Yuri Gordienko, Sergii Stirenko
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Big Data and Cognitive Computing
Subjects:
machine learning
computer vision
deep neural network
classification
MobileNetV3
multi-backbone
Online Access:https://www.mdpi.com/2504-2289/9/5/115
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