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Improved research on coral bleaching detection model based on FCOS model.
- Source :
-
Marine environmental research [Mar Environ Res] 2024 Sep; Vol. 200, pp. 106644. Date of Electronic Publication: 2024 Jul 11. - Publication Year :
- 2024
-
Abstract
- Coral bleaching detection is vital for assessing coral reef health. This paper introduces FCOS&#95;EfficientNET, an improved model that enhances accuracy, recall, and real-time performance in coral bleaching detection. Utilizing EfficientNet as the backbone, the model optimizes parameter throughput. We adopt the ReLU activation function and utilize cosine similarity and softmax to assign weights to datasets, modifying the attention structure to reduce memory consumption. The model also integrates BiFPN for better feature extraction and employs an improved training method to enhance detection accuracy. To cater to different scenarios, we have developed four variants: FCOS&#95;EfficientNETb0, FCOS&#95;EfficientNETb1, FCOS&#95;EfficientNETb2, and FCOS&#95;EfficientNETb3. Experimental results on the MS COCO dataset show that FCOS&#95;EfficientNETb3 achieves a mean average precision (mAP) of 48.5%, while FCOS&#95;EfficientNETb0 reaches a frame rate of 167.17 fps, highlighting the superior performance of the series. On a custom coral bleaching detection dataset, FCOS&#95;EfficientNETb3 achieves 81.5% accuracy and a 59.3% recall rate, demonstrating the effectiveness of the model. FCOS&#95;EfficientNETb1 and FCOS&#95;EfficientNETb2 offer a balance between operations per second, frame rate, and mAP, making them suitable for mobile and edge computing. These models effectively track movement or changes in marine traffic around coral reefs with moderate fps and recall rates.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1879-0291
- Volume :
- 200
- Database :
- MEDLINE
- Journal :
- Marine environmental research
- Publication Type :
- Academic Journal
- Accession number :
- 39003799
- Full Text :
- https://doi.org/10.1016/j.marenvres.2024.106644