SpermYOLO: A Coordinated YOLO-Based Detector for Accurate and Efficient Sperm and Impurity Detection in Microscopic Images

arXiv:2609.14278 · cs.CV, cs.AI · Submitted 2026-09-13 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-13

Updated: 2026-09-13

Comments: 51 pages, 10 figures

Code: https://github.com/ElvisChen7/SpermYOLO

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Ablation — 16× in this paper · explained in 1 episode
• Benchmark — 14× in this paper · explained in 2 episodes
• Feature Extraction — 12× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Adaptation — 9× in this paper · explained in 1 episode
• Transformer — 6× in this paper · explained in 2 episodes
• Aggregation — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Ablation Studies — 3× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Architectural Adaptation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• European Conference on Computer Vision — 2× in this paper
• Failure Modes — 2× in this paper · explained in 3 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Multi-Scale Feature Fusion Module — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 1× in this paper
• F1 Score — 1× in this paper · explained in 3 episodes
• Guided attention — 1× in this paper · explained in 2 episodes
• Hypergraph — 1× in this paper · explained in 2 episodes
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• International Symposium on Biomedical Imaging — 1× in this paper
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Stochastic Gradient Descent (SGD) — 1× in this paper · explained in 5 episodes
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications
• YOLOv11: An Overview of the Key Architectural Enhancements
• YOLOv12: Attention-Centric Real-Time Object Detectors
• YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception
• A Hybrid Transformer-Mamba Network for Single Image Deraining
• Depth Information Assisted Collaborative Mutual Promotion Network for Single Image Dehazing
• DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention
• LSM-YOLO: A Compact and Effective ROI Detector for Medical Detection
• CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer
• Multi-Branch Auxiliary Fusion YOLO with Re-parameterization Heterogeneous Convolutional for accurate object detection
• No More Strided Convolutions or Pooling: A New CNN Building Block for Low-Resolution Images and Small Objects

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