Art Original

Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 14, No 2, June 2026 | Lightweight Enhancement Module for Efficient Sea Turtle Species Detection under Illumination Variation

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Sea turtle monitoring is crucial for maintaining ecosystem balance, although traditional methods are costly and inefficient. Object detection provides a foundation for autonomous monitoring by localizing sea turtles in their natural habitat. At the same time, recent deep learning models can operate in real-time. On the other hand, underwater detection remains challenging due to extreme illumination, underwater blur, and underwater distortions, which obscure key features from the background. To address these issues, this work proposes a new sea turtle detector, based on a modified YOLOv12-nano model that incorporates a lightweight enhancement module to improve robustness under diverse illumination. The network introduced Efficient Spatial Convolution (ESC) at the end of the backbone to improve the representation of high-level features. It involves Dual Spatial Convolution (DSC) to improve backbone feature extraction with a large kernel size while preserving efficiency. The Lite module is designed to enrich feature diversity and selectively enhance the quality of high-level features. These modifications significantly enhance detection performance under diverse underwater lighting conditions. The proposed network achieves higher precision than the original YOLOv12-nano while maintaining efficiency, making it well-suited for deployment on low-cost devices.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

050

Penerbit

: Indonesian Journal of Electrical Engineering and Informatics (IJEEI)., 2026

Deskripsi Fisik

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Bahasa

English

ISBN/ISSN

2089-3272

Klasifikasi

050

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

JURNAL

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

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