Comparing YOLOv11 and YOLOv8 for instance segmentation of occluded and non-occluded immature green fruits in complex orchard environment
cs.CV
Submitted: 2024-10-24
Updated: 2026-09-24
Code: https://github.com/ultralytics/yolov5
Terminology
Sources
- Integrating YOLO11 and Convolution Block Attention Module for Multi-Season Segmentation of Tree Trunks and Branches in Commercial Apple Orchards
- Zero-Shot Automatic Annotation and Instance Segmentation using LLM-Generated Datasets: Eliminating Field Imaging and Manual Annotation for Deep Learning Model Development
- YOLOv4: Optimal Speed and Accuracy of Object Detection
- YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications
- YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
- YOLOv10: Real-Time End-to-End Object Detection
- YOLO advances to its genesis: a decadal and comprehensive review of the You Only Look Once (YOLO) series
- Comprehensive Performance Evaluation of YOLOv12, YOLO11, YOLOv10, YOLOv9 and YOLOv8 on Detecting and Counting Fruitlet in Complex Orchard Environments
- YOLO11 and Vision Transformers based 3D Pose Estimation of Immature Green Fruits in Commercial Apple Orchards for Robotic Thinning
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