Tiny-MobileNet-SE: A Hybrid Lightweight CNN Architecture for Resource-Constrained IoT Devices

Tiny-MobileNet-SE: A Hybrid Lightweight CNN Architecture for Resource-Constrained IoT Devices

Traditional Convolutional Neural Network (CNN) architectures face challenges in deployment on resource-constrained devices such as Internet of Things (IoT) platforms, mobile applications, and drones due to their computational intensity and memory requirements. This limitation motivates the developme...

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Bibliographic Details
Main Authors: Jean Pierre Nyakuri, Celestin Nkundineza, Omar Gatera, Kizito Nkurikiyeyezu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep learning (DL)
convolutional neural network (CNN)
Internet of Things (IoT)
resource constrained environment
computational efficiency
Tiny-MobileNet-SE
Online Access:https://ieeexplore.ieee.org/document/11048474/
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https://ieeexplore.ieee.org/document/11048474/

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