1、会议 (INPROCEEDINGS)
示例:
@INPROCEEDINGS{rcnn,
title={Rich feature hierarchies for accurate object detection and semantic segmentation},
author={Girshick, Ross and Donahue, Jeff and Darrell, Trevor and Malik, Jitendra},
booktitle={2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
pages={580--587},
year={2014},
organization={IEEE}
}
2、期刊(ARTICLE)
示例:
@ARTICLE{fasterrcnn,
author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks},
year={2017},
volume={39},
number={6},
pages={1137-1149},
3、学位论文(PHDTHESIS)或者(MASTER)
示例:
@PHDTHESIS{RN2,
author = {陈琳},
title = {基于深度学习的SAR图像目标识别与分类},
school = {山东大学},
year = {2021},
language = {zh}
}
4、在线文章或者资料(ONLINE)
示例:
@online{CN9,
Author = {Gevorgyan, Zhora},
Title = {SIoU Loss: More Powerful Learning for Bounding Box Regression},
Year = {2022},
Eprint = {2205.12740},
Eprinttype = {arXiv},
url = {https://arxiv.org/pdf/2205.12740.pdf}
}
关于一类特殊的文献引用,出自于arXiv文章
5、arXiv
目前搜索到的是两种引用格式,也不清楚哪一种格式正确,欢迎大家来一起讨论!!一种是作为网络出版的,链接为论文PDF的链接。一种作为期刊出版的,期刊名称为arXiv preprint arXiv。
示例一:
@online{CN9,
Author = {Gevorgyan, Zhora},
Title = {SIoU Loss: More Powerful Learning for Bounding Box Regression},
Year = {2022},
Eprint = {2205.12740},
Eprinttype = {arXiv},
url = {https://arxiv.org/pdf/2205.12740.pdf}
}
示例二:
@ARTICLE{yolo4,
title={Yolov4: Optimal speed and accuracy of object detection},
author={Bochkovskiy, Alexey and Wang, Chien-Yao and Liao, Hong-Yuan Mark},
journal={arXiv preprint arXiv:2004.10934},
year={2020}
}
如果重新生成参考文献目标,需要先编译.bbl文件,才能生成并覆盖原有记录。建议先删除.bbl文件,重新编译.tex整个工程。
1)中文文献“等”的修改:
需要指定关键词language={zh}
示例:
在这里插入代码片@ARTICLE{张佳欣,
title={改进 YOLOv3 的 SAR 图像舰船目标检测.},
author={张佳欣 and 王华力},
journal={Journal of Signal Processing},
volume={37},
number={9},
year={2021},
language = {zh}
}
详细的逻辑代码在.bst文件中,.bst文件详细写了每一种类型文献的解析逻辑。
代码截取:
2)关于删减文献中出版地的信息
由于该模板的学位论文文献表达必须要有出版地,该关键词是必选项:
解决方案可以参考这篇博客:
https://blog.csdn.net/oZhengTuManMan/article/details/124112117
EI:官方可批量
IEEE:官方可批量
谷歌学术(推荐):检索比较全,比较快,但是个别会出现问题,需要仔细核对。