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Research on Object Detection in Animal Images Based on Convolutional Neural Networks


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Gao Hui. Research on Video Object Detection Algorithm Based on Deep Learning [D]. University of Electronic Science and Technology of China, 2021. Hui. Gao Research on Video Object Detection Algorithm Based on Deep Learning [D] . University of Electronic Science and Technology of China , 2021 . Search in Google Scholar

Zhang Xin. Image Recognition System of Engineering Vehicle Equipment Based on Deep Learning [D]. Xidian University, 2021. Xin. Zhang Image Recognition System of Engineering Vehicle Equipment Based on Deep Learning [D] . Xidian University , 2021 . Search in Google Scholar

Zhao Yongqiang, Rao Yuan, Dong Shipeng et al. Review of Deep learning object detection methods [J]. Journal of Image and Graphics, 2019, 25(04):629–654. Yongqiang Zhao Yuan Rao Shipeng Dong Review of Deep learning object detection methods [J] . Journal of Image and Graphics , 2019 , 25 ( 04 ): 629 654 . Search in Google Scholar

Fan Lili, Zhao Hongwei, Zhao Haoyu, et al. Optics and Precision Engineering, 2020, 28(05):1152–1164. Lili Fan Hongwei Zhao Haoyu Zhao Optics and Precision Engineering , 2020 , 28 ( 05 ): 1152 1164 . Search in Google Scholar

Wang Yuzheng, Cheng Yuan, Bi Hai et al. Marine single-cell algae recognition algorithm based on deep learning VGG network model [J]. Journal of Dalian Ocean University, 2021, 36(02):334–339. Yuzheng Wang Yuan Cheng Hai Bi Marine single-cell algae recognition algorithm based on deep learning VGG network model [J] . Journal of Dalian Ocean University , 2021 , 36 ( 02 ): 334 339 . Search in Google Scholar

Trnovszky T, Kamencay P, Orjesek R, et al. Animal recognition system based on convolutional neural network [J]. Advances in Electrical and Electronic Engineering, 2017, 15(3):517. Trnovszky T Kamencay P Orjesek R Animal recognition system based on convolutional neural network [J] . Advances in Electrical and Electronic Engineering , 2017 , 15 ( 3):517. Search in Google Scholar

Schneider S, Taylor G W, Kremer S. Deep learning object detection methods for ecological camera trap data [C]. IEEE Conference on Computer and Robot Vision, 2018: 321–328. Schneider S Taylor G W Kremer S. Deep learning object detection methods for ecological camera trap data [C] . IEEE Conference on Computer and Robot Vision , 2018 : 321 328 . Search in Google Scholar

Li Anqi. Research on automatic recognition of wildlife monitoring images based on Convolutional neural networks [D]. Beijing Forestry University, 2020. Anqi. Li Research on automatic recognition of wildlife monitoring images based on Convolutional neural networks [D] . Beijing Forestry University , 2020 . Search in Google Scholar

Cheng Z A. Automatic recognition of terrestrial wildlife in Inner Mongolia based on deep convolutional neural networks [D]. Beijing Forestry University, 2019. Cheng Z A. Automatic recognition of terrestrial wildlife in Inner Mongolia based on deep convolutional neural networks [D] . Beijing Forestry University , 2019 . Search in Google Scholar

Ma Linlin, Ma Jianxin, Han Jiafang et al. Research on Object Detection Algorithm based on YOLOv5s [J]. Computer Knowledge and Technology, 2021, 17(23):100–103. Linlin Ma Jianxin Ma Jiafang Han Research on Object Detection Algorithm based on YOLOv5s [J] . Computer Knowledge and Technology , 2021 , 17 ( 23 ): 100 103 . Search in Google Scholar

Zhou Wenhui, JIA Yonghong, Jiao Yang. Research on detection method of Chinese sturgeon in underwater video [J]. Computer Science and Applications, 2022, 12(8): 1998–2005. Wenhui Zhou Yonghong JIA Yang Jiao Research on detection method of Chinese sturgeon in underwater video [J] . Computer Science and Applications , 2022 , 12 ( 8 ): 1998 2005 . Search in Google Scholar

Fan Youchen, Ma Xu, Ma Shuli et al. Evaluation method of laser interference effect based on deep learning [J]. Infrared and Laser Engineering, 2021, 50(S2): 39–45. Youchen Fan Xu Ma Shuli Ma Evaluation method of laser interference effect based on deep learning [J] . Infrared and Laser Engineering , 2021 , 50 ( S2 ): 39 45 . Search in Google Scholar

Lin Sike, Chen Jinwei, Huang Sihua. Research on Student Behavior Detection based on Deep Learning [J]. China Journal of Multimedia and Network Teaching (Mid-day), 2022(06):237–240. Sike Lin Jinwei Chen Sihua Huang Research on Student Behavior Detection based on Deep Learning [J] . China Journal of Multimedia and Network Teaching (Mid-day) , 2022 ( 06 ): 237 240 . Search in Google Scholar

Jin Y. Research on pig quantity monitoring method based on machine vision [D]. Jiangxi Agricultural University, 2021. Jin Y. Research on pig quantity monitoring method based on machine vision [D] . Jiangxi Agricultural University , 2021 . Search in Google Scholar

He Yuzhe, He Ning, Zhang Ren et al. Research on Training Unbalance of Deep Learning-oriented object detection Model [J]. Computer Engineering and Applications, 2022, 58(05):172–178. Yuzhe He Ning He Ren Zhang Research on Training Unbalance of Deep Learning-oriented object detection Model [J] . Computer Engineering and Applications , 2022 , 58 ( 05 ): 172 178 . Search in Google Scholar

Xu Bo. Research on Object Detection and Semantic Segmentation Algorithms based on Deep Learning [D]. Northeastern University, 2019. Bo. Xu Research on Object Detection and Semantic Segmentation Algorithms based on Deep Learning [D] . Northeastern University , 2019 . Search in Google Scholar

eISSN:
2470-8038
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Inglés
Calendario de la edición:
4 veces al año
Temas de la revista:
Computer Sciences, other