mlsanityData to 14 Oct 2026

BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection

arXiv 2309.12585 ↗First posted 22 Sep 2023cs.CV eess.SP stat.APcited by 7

Not on the map. Why?

Abstract (arXiv)

You Only Look Once (YOLO)-based object detectors have shown remarkable accuracy for automated brain tumor detection. In this paper, we develop a novel BGF-YOLO architecture by incorporating Bi-level routing attention, Generalized feature pyramid networks, and Fourth detecting head into YOLOv8. BGF-YOLO contains an attention mechanism to focus more on important features, and feature pyramid networks to enrich feature representation by merging high-level semantic features with spatial details. Furthermore, we investigate the effect of different attention mechanisms and feature fusions, detection head architectures on brain tumor detection accuracy. Experimental results show that BGF-YOLO gives a 4.7% absolute increase of mAP50 compared to YOLOv8x, and achieves state-of-the-art on the brain tumor detection dataset Br35H. The code is available at https://github.com/mkang315/BGF-YOLO.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 23 of its 37 references that are in the map. First posted on arXiv 22 Sep 2023.

Builds on

23 of 37 references.

References · 23

  1. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  2. 2017Squeeze-and-Excitation Networkscited by 4,789
  3. 2018CBAM: Convolutional Block Attention Modulecited by 2,477
  4. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,368
  5. 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,020
  6. 2018Path Aggregation Network for Instance Segmentationcited by 798
  7. 2019ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networkscited by 575
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  9. 2020Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detectioncited by 409
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  11. 2021Coordinate Attention for Efficient Mobile Network Designcited by 241
  12. 2020VarifocalNet: An IoU-aware Dense Object Detectorcited by 231
11 more
  1. 2023BiFormer: Vision Transformer with Bi-Level Routing Attentioncited by 151
  2. 2020Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detectioncited by 104
  3. 2021Focal and Efficient IOU Loss for Accurate Bounding Box Regressioncited by 57
  4. 2022SIoU Loss: More Powerful Learning for Bounding Box Regressioncited by 49
  5. 2022DAMO-YOLO : A Report on Real-Time Object Detection Designcited by 38
  6. 2023Wise-IoU: Bounding Box Regression Loss with Dynamic Focusing Mechanismcited by 30
  7. 2022GiraffeDet: A Heavy-Neck Paradigm for Object Detectioncited by 17
  8. 2023AFPN: Asymptotic Feature Pyramid Network for Object Detectioncited by 17
  9. 2023RFAConv: Receptive-Field Attention Convolution for Improving Convolutional Neural Networkscited by 10
  10. 2023RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detectioncited by 5
  11. 2023Improved YOLOv8 Detection Algorithm in Security Inspection Imagecited by 2

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Cited by year

Citing papers per year: 2024: 3; 2025: 4.

7 papers.

  1. 2024SOD-YOLOv8 -- Enhancing YOLOv8 for Small Object Detection in Traffic Scenescited by 3
  2. 2025MedROV: Towards Real-Time Open-Vocabulary Detection Across Diverse Medical Imaging Modalitiescited by 2
  3. 2024PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI Slicescited by 1
  4. 2025SCC-YOLO: An Improved Object Detector for Assisting in Brain Tumor Diagnosiscited by 1
  5. 2024Improving Generalization Performance of YOLOv8 for Camera Trap Object Detectioncited by 0
  6. 2025Efficient SAR Vessel Detection for FPGA-Based On-Satellite Sensingcited by 0
  7. 2025Synergistic Modality-and-Slice Memory Framework for Cross-Modal 3D Brain Tumor Segmentationcited by 0