Automated Species Identification in Camera Trap Images for Wildlife Conservation
Wildlife conservation involves protecting, preserving, and managing wildlife species and their habitats. With today's rapid pace of human development, climate change, and other unsustainable practices, the need for wildlife conservation has heightened. Despite significant progress in species identification using deep-learning models, significant challenges still remain in effectively detecting small animals in low-contrast trap images due to limited feature extraction capabilities. This thesis presents a novel end-to-end framework integrating a self-attention mechanism to address these limitations. The proposed architecture involves a Swin-BiFPN backbone integrated in a Faster RCNN detect...
| Authors | Nowshin Amin, Nafisa Tabassum Oyshi, Tahmid Abrar Zidan et al. |
|---|---|
| Primary category | cs.CV |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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