| [1]樊湘鹏，周建平，许燕，等.基于优化Faster R-CNN的棉花苗
期杂草识别与定位[J].农业机械学报，2021,52(05)：26-
34.
[2]Simonyan K,Zisserman A.Very deep convolutionalnetworks for
large-scale image recognition[C.Intemational Conference on
Learing Representations.Computational and Biological Learing
Society,2015.
[3]Ren S,He K,Girshick R,et al.Faster R-CNN:Towards Real-
Time Object Detection with Region Proposal Networks J].IEEE
Transactions on Pattern Analysis Machine Intelligence,2017,39
(6):1137-1149.
[4姜红花，张传银，张昭，等.基于Mask R-CNN的玉米田间杂
草检测方法[J].农业机械学报，2020,51(06)：220-228，
247.
[5]He K,Gkioxari G,Piotr Doll ar,et al.Mask R-CNN [J].
IEEE Transactions on Patter Analysis Machine Intelligence,
2017.
[6]赵辉，曹字航，岳有军，王红君.基于改进DenseNet的田间杂
草识别[J].农业工程学报，2021,37(18)：136-142.
[7]权龙哲，夏福霖，姜伟，等.基于YOL0v4卷积神经网络的农田苗草识别研究[J].东北农业大学学报，2021,51(07)：
89-98.
[8]Bochkovskiy A,Wan C Y G,Liao H.YOL0v4:Optimalspeed
and accuracy of object detection C].2020IEEE/CVF Conference
on Computer Vision and PatterRecognition CVPR )IEEE,
2020.
[9]Wang C Y,Liao H Y M,Wu Y H,et al.CSPNet:A new back-
bone that can enhance learning capability of CNN C].Proceedings
of the 2020 IEEE/CVF Conference on Computer Vision and Patter-
RecognitionWorkshops (CVPRW).Seattle:IEEE,2020.
[10]He K M,Zhang X Y,Ren S Q,et al.Deep residual leaming for
image recognition C].Proceedings of the 2016 IEEE Conference
on Computer Vision and PatterRecognition.Las Vegas:IEEE,
2016.
[11]Liu S,Qi L,Qin H F,et al.Path aggregation network for in-
stance segmentation C].Proceedings of the 2018 IEEE/CVF
Conference on Computer Vision and Patter Recognition.Salt Lake
City:IEEE,2018.
[12]Lin T Y,Dollar P,Girshick R,et al.Feature pyramid networks
for object detection [C].Proceedings of the 2017 IEEE Confer-
ence on Computer Vision and Patter Recognition.Honolulu:
IEEE,2017.
[13]Zhang X Y,Zhou X Y,Lin M X,et al.ShuffleNet:An ex-
tremely efficient convolutional neural network for mobile devices
[C].Proceedings of the 2018 IEEE/CVF Conference on Computer
Vision and Pattern Recognition.Salt Lake City:IEEE,2018.
[14]Li H,Li J,Wei H,et al.Slim-neck by GSConv:a lightweight-
design for real-time detector architectures [J].Joural of Real-
Time Image Processing,2024,21 (3).
[15]Ning T,Pan S,Zhou J.YOLOv7-SIMAM:An effective method
for SAR ship detection[C.2024 4th International Conference on
Neural Networks,Information and Communication NNICE )
2024. |
