Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Jiang, Zhaoyin, Huang, Shucheng, Li, Mingxing (2024) A Pedestrian Detection Network Based on an Attention Mechanism and Pose Information. Applied Sciences, 14 (18). doi:10.3390/app14188214

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleA Pedestrian Detection Network Based on an Attention Mechanism and Pose Information
JournalApplied Sciences
AuthorsJiang, ZhaoyinAuthor
Huang, ShuchengAuthor
Li, MingxingAuthor
Year2024 (September 12)Volume14
Issue18
PublisherMDPI AG
DOIdoi:10.3390/app14188214Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID17604817Long-form Identifiermindat:1:5:17604817:6
GUID0
Full ReferenceJiang, Zhaoyin, Huang, Shucheng, Li, Mingxing (2024) A Pedestrian Detection Network Based on an Attention Mechanism and Pose Information. Applied Sciences, 14 (18). doi:10.3390/app14188214
Plain TextJiang, Zhaoyin, Huang, Shucheng, Li, Mingxing (2024) A Pedestrian Detection Network Based on an Attention Mechanism and Pose Information. Applied Sciences, 14 (18). doi:10.3390/app14188214
In(2024, September) Applied Sciences Vol. 14 (18). MDPI AG

See Also

These are possibly similar items as determined by title/reference text matching only.

Gong, Han; Li, Tian; Wang, Lijuan; Huang, Shucheng; Li, Mingxing (2025) An Improved YOLOv8-Based Dense Pedestrian Detection Method with Multi-Scale Fusion and Linear Spatial Attention. Applied Sciences, 15 (10). doi:10.3390/app15105518
Li, Li, Gui, Xiangquan, Lv, Rui (2023) Recommendation Algorithm Based on Heterogeneous Information Network and Attention Mechanism. Applied Sciences, 14 (1) 353 doi:10.3390/app14010353
Xie, Jianwu, Li, Weiwei, Liu, Wenwen, Chen, Hang (2024) A Road Crack Detection Method Based on Residual and Attention Mechanism. Applied Sciences, 14 (13) 5749 doi:10.3390/app14135749
Wu, Nengkai, Jia, Dongyao, Li, Ziqi, He, Zihao (2024) Weak Edge Target Segmentation Network Based on Dual Attention Mechanism. Applied Sciences, 14 (19). doi:10.3390/app14198963
Li, Chang, Wang, Yiding, Liu, Xiaoming (2022) A Multi-Pedestrian Tracking Algorithm for Dense Scenes Based on an Attention Mechanism and Dual Data Association. Applied Sciences, 12 (19) 9597 doi:10.3390/app12199597
Zhao, Pei, Ling, Guang, Song, Xiangxiang (2024) ELFNet: An Effective Electricity Load Forecasting Model Based on a Deep Convolutional Neural Network with a Double-Attention Mechanism. Applied Sciences, 14 (14) 6270 doi:10.3390/app14146270
Li, Xinhai, Liang, Yong, Yang, Zhenhao, Li, Jie (2025) Pedestrian Trajectory Prediction Based on Dual Social Graph Attention Network. Applied Sciences, 15 (8). doi:10.3390/app15084285
Wang, Feilong, Yang, Xiaobing, Wei, Juan (2024) YOLO-ESL: An Enhanced Pedestrian Recognition Network Based on YOLO. Applied Sciences, 14 (20). doi:10.3390/app14209588
Li, Hongmei, Huang, Jinying, Gao, Minjuan, Yang, Luxia, Bao, Yichen (2022) Multi-View Information Fusion Fault Diagnosis Method Based on Attention Mechanism and Convolutional Neural Network. Applied Sciences, 12 (22) 11410 doi:10.3390/app122211410
Chen, Zehui, Wang, Changyuan, Wu, Gongpu (2024) Pupil Refinement Recognition Method Based on Deep Residual Network and Attention Mechanism. Applied Sciences, 14 (23). doi:10.3390/app142310971
Ye, Mu, Zhang, Weiwei, Cao, Pengcheng, Liu, Kangan (2021) Driver Fatigue Detection Based on Residual Channel Attention Network and Head Pose Estimation. Applied Sciences, 11 (19) 9195pp. doi:10.3390/app11199195
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are Β© OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 31, 2025 04:25:05
Go to top of page