Enhancing maritime search and rescue with small object detection techniques
Del Trieste, Francesco (A.A. 2024/2025) Enhancing maritime search and rescue with small object detection techniques. Tesi di Laurea in Machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 126. [Master's Degree Thesis]
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Abstract/Index
Context of the maritime SAR sector. State of the Art. Current architectural paradigms. Literature review on small object detection. SOD applications in the maritime domain. Dataset. MOB dataset. Coast guard dataset. Model architecture: MaYOLOc. YOLOv8 architecture. Context integration through self-attention module: MaYOLOc. Training pipeline. Model evaluation. Metrics. Experiments and results. MaYOLOc explainability.
References
Bibliografia: pp. 105-110.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Machine learning |
| Thesis Supervisor: | Italiano, Giuseppe Francesco |
| Thesis Co-Supervisor: | Coppa, Emilio |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 19 Mar 2026 10:14 |
| Last Modified: | 19 Mar 2026 10:14 |
| URI: | https://tesi.luiss.it/id/eprint/45192 |
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