[1] LI T, FENG Q, QIU Q, et al. Occluded apple fruit detection and localization with a frustum-based point-cloud-processing approach for robotic harvesting[J]. Remote Sensing, 2022, 14(3): 482.
[2] 王超学, 祁昕, 马罡, 等. 基于YOLO V3的葡萄病害人工智能识别系统[J]. 植物保护, 2022, 48(6): 278-288.
WANG C X, QI X, MA G, et al. Intelligent identification system of grape diseases based on YOLO V3[J]. Plant Protection, 2022, 48(6): 278-288.
[3] PéREZ-ZAVALA R, TORRES-TORRITI M, CHEEIN F A, et al. A pattern recognition strategy for visual grape bunch detection in vineyards[J]. Computers and Electronics in Agriculture, 2018, 151: 136-149.
[4] KOIRALA A, WALSH K B, WANG Z. Attempting to estimate the unseen—correction for occluded fruit in tree fruit load estimation by machine vision with deep learning[J]. Agronomy, 2021, 11(2): 347.
[5] ZHAO R, ZHU Y, LI Y. An end-to-end lightweight model for grape and picking point simultaneous detection[J]. Biosystems Engineering, 2022, 223: 174-188.
[6] 蒋心璐, 陈天恩, 王聪, 等. 农业害虫检测的深度学习算法综述[J]. 计算机工程与应用, 2023, 59(6): 30-44.
JIANG X L, CHEN T E, WANG C, et al. Survey of deep learning algorithms for agricultural pest detection[J]. Computer Engineering and Applications, 2023, 59(6): 30-44.
[7] KIERDORF J, WEBER I, KICHERER A, et al. Behind the leaves: estimation of occluded grapevine berries with conditional generative adversarial networks[J]. Frontiers in Artificial Intelligence, 2022, 5: 830026.
[8] DI GENNARO S F, TOSCANO P, CINAT P, et al. A low-cost and unsupervised image recognition methodology for yield estimation in a vineyard[J]. Frontiers in Plant Science, 2019, 10: 559.
[9] JIA W, ZHANG Z, SHAO W, et al. RS-NET: robust segmentation of green overlapped apples[J]. Precision Agriculture, 2022, 23(2): 492-513.
[10] LIU X, ZHAO D, JIA W, et al. Cucumber fruits detection in greenhouses based on instance segmentation[J]. IEEE Access, 2019, 7: 139635-139642.
[11] 黄磊磊, 苗玉彬. 基于深度学习的重叠柑橘分割与形态复原[J]. 农机化研究, 2023, 45(10): 70-75.
HUANG L L, MIAO Y B. Overlapping citrus segmentation and morphological restoration based on deep learning[J]. Journal of Agricultural Mechanization Research, 2023, 45(10): 70-75.
[12] TANG C, CHEN H, LI X, et al. Look closer to segment better: boundary patch refinement for instance segmentation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Nashville, Jun 20-25, 2021. Piscataway, NJ: IEEE, 2021: 13926-13935.
[13] CHENG T, WANG X, HUANG L, et al. Boundary-preserving mask R-CNN[C]//16th European Conference on Computer Vision, Glasgow, Aug 23-28, 2020. Cham: Springer International Publishing, 2020: 660-676.
[14] KE L, DANELLJAN M, LI X, et al. Mask transfiner for high-quality instance segmentation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, Jun 19-24, 2022. Piscataway, NJ: IEEE, 2022: 4412-4421.
[15] ZHANG Z, CUI Z, XU C, et al. Pattern-affinitive propagation across depth, surface normal and semantic segmentation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, Jun 16-20, 2019. Piscataway, NJ: IEEE, 2019: 4106-4115.
[16] VANDENHENDE S, GEORGOULIS S, VAN GOOL L. MTI-Net: multi-scale task interaction networks for multi-task learning[C]//16th European Conference on Computer Vision, Glasgow, Aug 23-28, 2020. Cham, Switzerland: Springer International Publishing, 2020: 527-543.
[17] HE K, GKIOXARI G, DOLLáR P, et al. Mask R-CNN[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 42(2): 386-397.
[18] ACUNA D, KAR A, FIDLER S. Devil is in the edges: learning semantic boundaries from noisy annotations[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, Jun 16-20, 2019. Piscataway, NJ: IEEE, 2019: 11075-11083.
[19] XIE S, TU Z. Holistically-nested edge detection[J]. International Journal of Computer Vision, 2017, 125(1/3): 3-18.
[20] CHENG B, GIRSHICK R, DOLLáR P, et al. Boundary IOU: improving object-centric image segmentation evaluation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Nashville, Jun 19-25, 2021. Piscataway, NJ: IEEE, 2021: 15334-15342.
[21] BOLYA D, ZHOU C, XIAO F, et al. Yolact: real-time instance segmentation[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision, Seoul, Oct 27-Nov 2 2019. Piscataway, NJ: IEEE, 2019: 9157-9166.
[22] WANG X, ZHANG R, KONG T, et al. Solov2: dynamic and fast instance segmentation[C]//Advances in Neural Information Processing Systems, 2020: 17721-17732.
[23] KIRILLOV A, WU Y, HE K, et al. Pointrend: image segmentation as rendering[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, Jun 14-19, 2020. Piscataway, NJ: IEEE, 2020: 9799-9808. |