Camera Trap

Camera traps are automated imaging systems used for wildlife monitoring, primarily aiming to efficiently collect and analyze data on species presence, abundance, and behavior. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs) and other architectures like Faster-RCNN and transformers, often incorporating techniques like active learning and two-phase training to address challenges posed by imbalanced datasets and limited labeled data. These advancements are significantly improving the efficiency and accuracy of biodiversity assessments, enabling large-scale ecological studies and informing conservation efforts with less manual effort. Furthermore, research is exploring innovative approaches such as multimodal knowledge graphs and motion-based compression to enhance data analysis and reduce resource constraints in remote settings.