Optimizing YOLO27, YOLO26, YOLO11, and YOLOv8 for Fine-Grained Small-Object Detection and Segmentation in Complex Orchard Environments

arXiv:2608.23636 · cs.CV · Submitted 2026-08-23 · Read on arXiv

cs.CV

Submitted: 2026-08-23

Updated: 2026-09-18

Terminology

• Accuracy — 54× in this paper · explained in 1 episode
• Instance Segmentation — 38× in this paper · explained in 3 episodes
• Benchmark — 27× in this paper · explained in 2 episodes
• Clustering — 9× in this paper · explained in 2 episodes
• Feature Extraction — 9× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Artificial Intelligence — 6× in this paper
• Consistency — 6× in this paper · explained in 3 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Data Augmentation — 5× in this paper · explained in 7 episodes
• Attention Mechanism — 4× in this paper · explained in 3 episodes
• Benchmarking — 4× in this paper · explained in 3 episodes
• Automatic Mixed Precision — 3× in this paper
• Core — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Slicing-Aided Hyper Inference — 3× in this paper
• Transfer Learning — 3× in this paper · explained in 10 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Segmentation Masks — 2× in this paper · explained in 2 episodes
• You Only Look Once — 2× in this paper
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Hypergraph — 1× in this paper · explained in 2 episodes
• National Institute of Food and Agriculture — 1× in this paper
• Point Clouds — 1× in this paper · explained in 2 episodes
• Test-time augmentation (TTA) — 1× in this paper · explained in 2 episodes
• United States Department of Agriculture — 1× in this paper

Sources

• Ultralytics YOLO Evolution: An Overview of YOLO27, YOLO26, YOLO11, YOLOv8, and YOLOv5 Object Detectors for Computer Vision and Pattern Recognition
• YOLOv3: An Incremental Improvement
• YOLO26: Key Architectural Enhancements and Performance Benchmarking for Real-Time Object Detection
• YOLOv12: Attention-Centric Real-Time Object Detectors
• YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception
• WildLive: Near Real-time Visual Wildlife Tracking onboard UAVs
• Small Object Detection: A Comprehensive Survey on Challenges, Techniques and Real-World Applications
• YOLOv8 to YOLO11: A Comprehensive Architecture In-depth Comparative Review
• Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models
• YOLOE-26: Integrating YOLO26 with YOLOE for Real-Time Open-Vocabulary Instance Segmentation

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