[1] Qin Y M, Chen W Y, Zhang P R et al. Research on scrap steel evaluation technology based on Faster-RCNN[C], 1-4(2021).

[2] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

[3] Xu W G, Xiao P C, Zhu L G et al. Classification and rating of steel scrap using deep learning[J]. Engineering Applications of Artificial Intelligence, 123, 106241(2023).

[4] Xu W G, Xiao P C, Zhu L G et al. An efficient treatment method of scrap intelligent rating based on machine vision[J]. Applied Intelligence, 54, 10912-10928(2024).

[5] Tu Q F, Li D W, Xie Q et al. Automated scrap steel grading via a hierarchical learning-based framework[J]. IEEE Transactions on Instrumentation and Measurement, 71, 5022313(2022).

[6] Lei J R, Huang S, Shen Z Q et al. LASER: LAyered ScenE recognition for visual intelligent recycling of steel scrap[J]. IEEE Transactions on Industrial Informatics, 21, 2927-2936(2025).

[7] Xu T F, Wang Y, Shi G K et al. Research progress in fundamental architecture of deep learning-based single object tracking method[J]. Acta Optica Sinica, 43, 1510003(2023).

[8] Ryali C, Hu Y T, Bolya D et al. Hiera: a hierarchical vision transformer without the bells-and-whistles[C], 202, 29441-29454(2023).

[9] Ravi N, Gabeur V, Hu Y T et al. SAM 2: segment anything in images and videos[EB/OL]. https:∥arxiv.org/abs/2408.00714

[10] Zhao X, Ding W C, An Y Q et al. Fast segment anything[EB/OL]. https:∥arxiv.org/abs/2306.12156v1

[11] Zhang Z Y, Cai H, Han S. EfficientViT-SAM: accelerated segment anything model without performance loss[C], 7859-7863(2024).

[12] Liu Y, Guo H T, Lu J et al. Remote sensing image change detection method based on adaptive boundary sensing[J]. Acta Optica Sinica, 44, 1828001(2024).

[13] Liu Q, Cao L, Tian S et al. Structure-aware multiscale hybrid network for change detection of remote sensing images[J]. Laser & Optoelectronics Progress, 61, 1428008(2024).

[14] Han X, Han L, Li L Z et al. Building change detection in high-resolution remote-sensing images based on deep learning[J]. Laser & Optoelectronics Progress, 59, 1001003(2022).

[15] Wang G H, Gao B B, Wang C J. How to reduce change detection to semantic segmentation[J]. Pattern Recognition, 138, 109384(2023).

[16] Redmon J, Farhadi A. YOLOv3: an incremental improvement[EB/OL]. https:∥arxiv.org/abs/1804.02767

[17] Sohan M, Sai Ram T, Rami Reddy C V. A review on YOLOv8 and its advancements[M]. Data intelligence and cognitive informatics, 529-545(2024).