arXiv:2112.13341
공식 코드 · Papers with Code
AlertTrap: A study on object detection in remote insects trap monitoring system using on-the-edge deep learning platform
원문 초록
Fruit flies are one of the most harmful insect species to fruit yields. In AlertTrap, implementation of SSD architecture with different state-of-the-art backbone feature extractors such as MobileNetV1 and MobileNetV2 appear to be potential solutions for the real-time detection problem. SSD-MobileNetV1 and SSD-MobileNetV2 perform well and result in [email omitted] of 0.957 and 1.0 respectively. YOLOv4-tiny outperforms the SSD family with 1.0 in [email omitted]; however, its throughput velocity is slightly slower.
함께 살펴볼 논문
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Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations
MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object Detection
Weakly-supervised Contrastive Learning with Quantity Prompts for Moving Infrared Small Target Detection
Improve Underwater Object Detection through YOLOv12 Architecture and Physics-informed Augmentation
Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning
LASFNet: A Lightweight Attention-Guided Self-Modulation Feature Fusion Network for Multimodal Object Detection
토론
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