[1] Ma W, Wang X, Yu J. A lightweight feature fusion single shot multibox detector for garbage detection[J]. IEEE Access, 8, 188577-188586(2020).

[2] Liu W, Anguelov D, Erhan D et al. SSD: single shot multibox detector[M]. Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, 9905, 21-37(2016).

[3] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

[4] Wen C H, Li J, Dong X. Intelligent domestic garbage recognition based on faster RCNN[J]. Laser & Optoelectronics Progress, 57, 201014(2020).

[5] 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).

[6] Howard A G, Zhu M L, Chen B et al. MobileNets: efficient convolutional neural networks for mobile vision applications[EB/OL]. https://arxiv.org/abs/1704.04861

[7] Feng J W, Tang X Y, Jiang X J et al. Garbage disposal of complex background based on deep learning with limited hardware resources[J]. IEEE Sensors Journal, 21, 21050-21058(2021).

[8] He K M, Gkioxari G, Dollár P et al. Mask R-CNN[C], 2980-2988(2017).

[9] Yu L, Pan G Y, Li M N. Garbage detection algorithm based on deep learning[C], 469-473(2021).

[10] Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934

[11] Yan X B, Yang Y, Feng L et al. A garbage classification method based on improved YOLOv5[C](2022).

[12] Huang Y T, Wen Q, Li Y Q. Lightweight domestic garbage detection method based on improved FPN[C], 370-374(2021).

[13] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection[C], 2999-3007(2017).

[14] Liu B H, Wang X P. Garbage detection algorithm based on YOLO v3[C], 784-788(2022).

[15] Hu J, Shen L, Sun G. Squeeze-and-excitation networks[C], 7132-7141(2018).

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

[17] Proença P F, Simões P. TACO: trash annotations in context for litter detection[EB/OL]. https://arxiv.org/abs/2003.06975

[18] Zhang Y Y, Zhou D S, Chen S Q et al. Single-image crowd counting via multi-column convolutional neural network[C], 589-597(2016).