Cross-task feature enhancement strategy in multi-task learning for harvesting Sichuan pepper-Reference-Cited by-同舟云学术

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Cross-task feature enhancement strategy in multi-task learning for harvesting Sichuan pepper

Published:2023-04 Issue: Volume:207 Page:107726
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Wang Yihan,Deng Xinglong,Luo Jianqiao,Li Bailin,Xiao Shide

Funder

Department of Science and Technology of Sichuan Province

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference37 articles.

1. Bochkovskiy, A., Wang, C.Y., Mark Liao, H.Y., 2020. YOLOv4: Optimal Speed and Accuracy of Object Detection. arXiv preprint arXiv:2004.10934.

2. Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F. Adam, H., 2018. Encoder-decoder with atrous separable convolution for semantic image segmentation. In: Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany, 8–14 September 2018; pp:801–818. 10.1007/978-3-030-01234-2_49.

3. Chu, P., Li, Z., Lammers, K., Lu, R., Liu, X., 2021. Deep learning-based apple detection using a suppression mask R-CNN. J. Pattern Recognit. Lett. 147;2021:206–211. 10.1016/j.patrec.2021.04.022.

4. Gao, Y., Bai, H.P., Jie, Z.P., Ma, J.Y., et al., 2020. MTL-NAS: Task-agnostic neural architecture search towards general-purpose multi-task learning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, WA, USA. 13-19 June 2020. pp:11543–11552. 10.1109/CVPR42600.2020.01156.

5. Gao, Y., Ma, J.Y., Zhao, M.B., et al., 2019. NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction. C. 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Long Beach, CA. JUN 16-20, 2019. pp: 3200-3209. 10.1109/CVPR.2019.00332.

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3. Aleatoric Uncertainty Based Label Distribuion Leanig for Pose Estimation of Sichuan Peppers;2023 China Automation Congress (CAC);2023-11-17

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