VM-YOLO: YOLO with VMamba for Strawberry Flowers Detection

• Published in: Plants (Basel) Vol. 14; no. 3; p. 468
• Main Authors: Wang, Yujin, Lin, Xueying, Xiang, Zhaowei, Su, Wen-Hao
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 05.02.2025; MDPI
• Subjects: Ablation; Accuracy; Agricultural equipment; Agricultural technology; Algorithms; Artificial neural networks; Computer vision; Crop damage; Damage detection; Datasets; Digital agriculture; Equipment and supplies; Experiments; Flowers; Image processing; Machine learning; Machine vision; Modules; Neural networks; object detection; Object recognition; Performance evaluation; Plant reproduction; Sensitivity analysis; state space model; State space models; Strawberries; strawberry flower; YOLOv8; object detection; state space model; strawberry flower; YOLOv8

Computer vision technology is widely used in smart agriculture, primarily because of its non-invasive nature, which avoids causing damage to delicate crops. Nevertheless, the deployment of computer vision algorithms on agricultural machinery with limited computing resources represents a significant...