mlsanityData to 7 Oct 2026

CPLOYO: A Pulmonary Nodule Detection Model with Multi-Scale Feature Fusion and Nonlinear Feature Learning

arXiv 2503.10045 ↗First posted 13 Mar 2025eess.IV cs.CVcited by 3

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Abstract (arXiv)

The integration of Internet of Things (IoT) technology in pulmonary nodule detection significantly enhances the intelligence and real-time capabilities of the detection system. Currently, lung nodule detection primarily focuses on the identification of solid nodules, but different types of lung nodules correspond to various forms of lung cancer. Multi-type detection contributes to improving the overall lung cancer detection rate and enhancing the cure rate. To achieve high sensitivity in nodule detection, targeted improvements were made to the YOLOv8 model. Firstly, the C2fRepViTCAMF module was introduced to augment the C2f module in the backbone, thereby enhancing detection accuracy for small lung nodules and achieving a lightweight model design. Secondly, the MSCAF module was incorporated to reconstruct the feature fusion section of the model, improving detection accuracy for lung nodules of varying scales. Furthermore, the KAN network was integrated into the model. By leveraging the KAN network's powerful nonlinear feature learning capability, detection accuracy for small lung nodules was further improved, and the model's generalization ability was enhanced. Tests conducted on the LUNA16 dataset demonstrate that the improved model outperforms the original model as well as other mainstream models such as YOLOv9 and RT-DETR across various evaluation metrics.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 25 of its 85 references that are in the map. First posted on arXiv 13 Mar 2025.

Builds on

25 of 85 references.

References · 25

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  4. 2024EITNet: An IoT-Enhanced Framework for Real-Time Basketball Action Recognitioncited by 8
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  12. 2025Intelligent logistics management robot path planning algorithm integrating transformer and GCN networkcited by 4
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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025MamNet: A Novel Hybrid Model for Time-Series Forecasting and Frequency Pattern Analysis in Network Trafficcited by 3
  2. 2025Research on Short-Video Platform User Decision-Making via Multimodal Temporal Modeling and Reinforcement Learningcited by 0
  3. 2025DT-NeRF: A Diffusion and Transformer-Based Optimization Approach for Neural Radiance Fields in 3D Reconstructioncited by 0