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YOLOv8-A: Enhanced Lightweight Object Detection with Nonlinear Feature Fusion and Mathematical Optimization for Precision Small Target Detection in Industrial Silicon Melting Processes

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17 mar 2025

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Carion, N., et al. (2020). End-to-end object detection with transformers. European Conference on Computer Vision, 213-229. DOI: 10.1007/978-3-030-58452-8_13b Carion N. ( 2020 ). End-to-end object detection with transformers . European Conference on Computer Vision , 213 - 229 . DOI: 10.1007/978-3-030-58452-8_13 Open DOISearch in Google Scholar

Feigelson, R. S. (2022). Crystal Growth History: Theory and Melt Growth Processes. Journal of Crystal Growth, 594, 126800. DOI: 10.1016/j.jcrysgro.2022.126800 Feigelson R. S. ( 2022 ). Crystal Growth History: Theory and Melt Growth Processes . Journal of Crystal Growth , 594 , 126800 . DOI: 10.1016/j.jcrysgro.2022.126800 Open DOISearch in Google Scholar

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014). Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 580–587. DOI: 10.1109/CVPR.2014.81 Girshick R. Donahue J. Darrell T. Malik J. ( 2014 ). Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation . IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 580 587 . DOI: 10.1109/CVPR.2014.81 Open DOISearch in Google Scholar

Han, K., Wang, Y., Zhang, Q., et al. (2020). GhostNet: More Features from Cheap Operations. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1580-1589. DOI:10.1109/CVPR42600.2020.00165 Han K. Wang Y. Zhang Q. ( 2020 ). GhostNet: More Features from Cheap Operations . IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 1580 - 1589 . DOI: 10.1109/CVPR42600.2020.00165 Open DOISearch in Google Scholar

Hussain, M. (2024). YOLOv1 to v8: Unveiling Each Variant – A Comprehensive Review ofYOLO. IEEE Access, 12, 42816-42833. DOI: 10.1109/ACCESS.2024.3060000 Hussain M. ( 2024 ). YOLOv1 to v8: Unveiling Each Variant – A Comprehensive Review ofYOLO . IEEE Access , 12 , 42816 - 42833 . DOI: 10.1109/ACCESS.2024.3060000 Open DOISearch in Google Scholar

Jocher, G. (2020). YOLOv5: Redefining real-time object detection. arXiv preprint arXiv:2012.08255. DOI: 10.48550/arXiv.2012.08255 Jocher G. ( 2020 ). YOLOv5: Redefining real-time object detection . arXiv preprint arXiv:2012.08255 . DOI: 10.48550/arXiv.2012.08255 Open DOISearch in Google Scholar

Li, N., Ye, T., Zhou, Z., & Zhang, P. (2024). Enhanced YOLOv8 with BiFPN-SimAM for Precise Defect Detection in Miniature Capacitors. Applied Sciences, 14(1), 429. DOI: 10.3390/app14010429 Li N. Ye T. Zhou Z. Zhang P. ( 2024 ). Enhanced YOLOv8 with BiFPN-SimAM for Precise Defect Detection in Miniature Capacitors . Applied Sciences , 14 ( 1 ), 429 . DOI: 10.3390/app14010429 Open DOISearch in Google Scholar

Lin, B., Li, X., & Chen, Y. (2022). Slim-neck by GSConv: A Better Design Paradigm of Detector Architectures for Autonomous Vehicles. arXiv preprint arXiv:2206.02424. DOI:10.48550/arXiv.2206.02424 Lin B. Li X. Chen Y. ( 2022 ). Slim-neck by GSConv: A Better Design Paradigm of Detector Architectures for Autonomous Vehicles . arXiv preprint arXiv:2206.02424 .DOI: 10.48550/arXiv.2206.02424 Open DOISearch in Google Scholar

Liu, D. (2015). Direct-drawn Monocrystalline Silicon Thermal System Modeling. In CZ Silicon Single Crystal Growth Modeling and Control. Beijing, China: Science Press, Chapter 4, pp. 68–73. Liu D. ( 2015 ). Direct-drawn Monocrystalline Silicon Thermal System Modeling . In CZ Silicon Single Crystal Growth Modeling and Control . Beijing, China : Science Press , Chapter 4, pp. 68 73 . Search in Google Scholar

Liu, X., Zhang, S., & Wang, M. (2023). Adaptive attention for small object detection in remote sensing images. Journal of Remote Sensing Technology, 34(4), 1123-1134. DOI: 10.1007/s13320-023-0654-9 Liu X. Zhang S. Wang M. ( 2023 ). Adaptive attention for small object detection in remote sensing images . Journal of Remote Sensing Technology , 34 ( 4 ), 1123 - 1134 . DOI: 10.1007/s13320-023-0654-9 Open DOISearch in Google Scholar

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779–788. DOI: 10.1109/CVPR.2016.91 Redmon J. Divvala S. Girshick R. Farhadi A. ( 2016 ). You Only Look Once: Unified, Real-Time Object Detection . IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 779 788 . DOI: 10.1109/CVPR.2016.91 Open DOISearch in Google Scholar

Tan, M., Pang, R., & Le, Q. V. (2020). EfficientDet: Scalable and Efficient Object Detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 10781-10790. DOI:10.1109/CVPR42600.2020.01078 Tan M. Pang R. Le Q. V. ( 2020 ). EfficientDet: Scalable and Efficient Object Detection . IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 10781 - 10790 . DOI: 10.1109/CVPR42600.2020.01078 Open DOISearch in Google Scholar

Wang, C., et al. (2022). YOLOv7: Trainable Bag of Freebies for real-time object detectors. arXiv preprint arXiv:2207.02696. DOI: 10.48550/arXiv.2207.02696 Wang C. ( 2022 ). YOLOv7: Trainable Bag of Freebies for real-time object detectors . arXiv preprint arXiv:2207.02696 . DOI: 10.48550/arXiv.2207.02696 Open DOISearch in Google Scholar

Wang, J., Zhang, X., & Zhao, Y. (2023). Dynamic Upsampling in YOLOv8 for Small Target Detection. IEEE Transactions on Image Processing, 32(7), 4561-4574. DOI: 10.1109/TIP.2023.3267890 Wang J. Zhang X. Zhao Y. ( 2023 ). Dynamic Upsampling in YOLOv8 for Small Target Detection . IEEE Transactions on Image Processing , 32 ( 7 ), 4561 - 4574 . DOI: 10.1109/TIP.2023.3267890 Open DOISearch in Google Scholar

Yang, C., et al. (2023). Real-time Detection of Industrial Defects Using Transformer-Based Architectures. Robotics and Automation Letters, 8(4), 1392–1405. DOI: 10.1109/LRA.2023.3245678 Yang C. ( 2023 ). Real-time Detection of Industrial Defects Using Transformer-Based Architectures . Robotics and Automation Letters , 8 ( 4 ), 1392 1405 . DOI: 10.1109/LRA.2023.3245678 Open DOISearch in Google Scholar

Yang, Z., Cheng, Y., & Huang, X. (2023). Research on the direct pull method single crystal silicon dislocation detection model based on improved YOLOv5 algorithm. Applied Optics, 44(5), 1022-1029. DOI: 10.1364/AO.44.005022 Yang Z. Cheng Y. Huang X. ( 2023 ). Research on the direct pull method single crystal silicon dislocation detection model based on improved YOLOv5 algorithm . Applied Optics , 44 ( 5 ), 1022 - 1029 . DOI: 10.1364/AO.44.005022 Open DOISearch in Google Scholar

Zhang, J., Liu, D., & Tang, Q.-W. (2022). The CNN deep learning-based melting process prediction of Czochralski monocrystalline silicon. IEEE Access, 10, 41986–41992. DOI:10.1109/ACCESS.2022.3160000 Zhang J. Liu D. Tang Q.-W. ( 2022 ). The CNN deep learning-based melting process prediction of Czochralski monocrystalline silicon . IEEE Access , 10 , 41986 41992 . DOI: 10.1109/ACCESS.2022.3160000 Open DOISearch in Google Scholar

Zhao, Y., & Cheng, D. (2011). Visual-based detection and monitoring of single crystal growth diameter. Manufacturing Automation, 7, 22-25.DOI: 10.1109/icdma.2011.343 Zhao Y. Cheng D. ( 2011 ). Visual-based detection and monitoring of single crystal growth diameter . Manufacturing Automation , 7 , 22 - 25 DOI: 10.1109/icdma.2011.343 . Open DOISearch in Google Scholar

Zhao, Y., & Wang, X. (2018). Research on temperature measurement technology for Czochralski crystal growth based on aperture pattern recognition. Journal of Sensing Technology, 31(4), 573-578. Zhao Y. Wang X. ( 2018 ). Research on temperature measurement technology for Czochralski crystal growth based on aperture pattern recognition . Journal of Sensing Technology , 31 ( 4 ), 573 - 578 . Search in Google Scholar

Zhao, Y., Cui, Y., & Wang, Z. (2023). Improved YOLOv5 Based on CBAM and BiFPN for Rice Pest and Disease Detection. International Conference on Computer, Internet of Things, and Smart City (CIoTSC), 29–36. DOI: 10.1109/CIoTSC.2023.3245680 Zhao Y. Cui Y. Wang Z. ( 2023 ). Improved YOLOv5 Based on CBAM and BiFPN for Rice Pest and Disease Detection . International Conference on Computer, Internet of Things, and Smart City (CIoTSC) , 29 36 . DOI: 10.1109/CIoTSC.2023.3245680 Open DOISearch in Google Scholar

Zhao, Z., Wang, P., & Xie, H. (2023). Improved Small-Object Detection with YOLOv8 Using BiFPN and GhostNet. Applied Sciences, 14(3), 1095-1105. DOI: 10.3390/app14031095 Zhao Z. Wang P. Xie H. ( 2023 ). Improved Small-Object Detection with YOLOv8 Using BiFPN and GhostNet . Applied Sciences , 14 ( 3 ), 1095 - 1105 . DOI: 10.3390/app14031095 Open DOISearch in Google Scholar

Zheng, X., Liu, Y., & Chen, Z. (2024). YOLOv8 for small target detection in the silicon melting process. Journal of Industrial Automation and Vision Systems, 35(4), 295-310. Zheng X. Liu Y. Chen Z. ( 2024 ). YOLOv8 for small target detection in the silicon melting process . Journal of Industrial Automation and Vision Systems , 35 ( 4 ), 295 - 310 . Search in Google Scholar

Wang, Y., Liu, H., & Chen, X. (2024). Efficient small object detection using multi-scale refinement networks. International Journal of Computer Vision, 50(1), 45-61. DOI: 10.1007/s11263-024-01678-2 Wang Y. Liu H. Chen X. ( 2024 ). Efficient small object detection using multi-scale refinement networks . International Journal of Computer Vision , 50 ( 1 ), 45 - 61 . DOI: 10.1007/s11263-024-01678-2 Open DOISearch in Google Scholar

Zhao, Y., & Cheng, D. (2023). A Study on High-Precision Detection in Industrial Inspection Using Enhanced YOLO Models. Journal of Advanced Computational Applications, 12(4), 145-167. DOI: 10.1016/j.aca.2023.145167 Zhao Y. Cheng D. ( 2023 ). A Study on High-Precision Detection in Industrial Inspection Using Enhanced YOLO Models . Journal of Advanced Computational Applications , 12 ( 4 ), 145 - 167 . DOI: 10.1016/j.aca.2023.145167 Open DOISearch in Google Scholar

Loshchilov, I., & Hutter, F. (2017). SGDR: Stochastic Gradient Descent with Warm Restarts. International Conference on Learning Representations (ICLR). DOI: 10.48550/arXiv.1608.03983 Loshchilov I. Hutter F. ( 2017 ). SGDR: Stochastic Gradient Descent with Warm Restarts . International Conference on Learning Representations (ICLR) . DOI: 10.48550/arXiv.1608.03983 Open DOISearch in Google Scholar

Zhao, Y., et al. (2023). Enhanced Feature Fusion for Lightweight Object Detection in Industrial Settings. Journal of Industrial AI Research, 10(2), 220-235. Zhao Y. ( 2023 ). Enhanced Feature Fusion for Lightweight Object Detection in Industrial Settings . Journal of Industrial AI Research , 10 ( 2 ), 220 - 235 . Search in Google Scholar

Yang, C., et al. (2023). Real-Time Detection of Industrial Defects Using Transformer-Based Architectures. Robotics and Automation Letters, 8(4), 1392–1405. DOI: 10.1109/LRA.2023.3245678 Yang C. ( 2023 ). Real-Time Detection of Industrial Defects Using Transformer-Based Architectures . Robotics and Automation Letters , 8 ( 4 ), 1392 1405 . DOI: 10.1109/LRA.2023.3245678 Open DOISearch in Google Scholar

Jocher, G. (2020). YOLOv5: Redefining Real-Time Object Detection. arXiv preprint arXiv:2012.08255. DOI: 10.48550/arXiv.2012.08255 Jocher G. ( 2020 ). YOLOv5: Redefining Real-Time Object Detection . arXiv preprint arXiv:2012.08255 . DOI: 10.48550/arXiv.2012.08255 Open DOISearch in Google Scholar

Liu, X., Zhao, Y., & Wang, J. (2023). Edge-Optimized YOLO for Real-Time Defect Detection. Advanced Robotics and Automation, 19(2), 102-118. Liu X. Zhao Y. Wang J. ( 2023 ). Edge-Optimized YOLO for Real-Time Defect Detection . Advanced Robotics and Automation , 19 ( 2 ), 102 - 118 . Search in Google Scholar

Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne