Page 71 - Read Online
P. 71

Zhuang et al. Intell Robot 2024;4(3):276-92  I http://dx.doi.org/10.20517/ir.2024.18  Page 292


               31. Howard A, Sandler M, Chen B, et al. Searching for MobileNetv3. In: 2019 IEEE/CVF International Conference on Computer Vision
                  (ICCV); 2019 Oct 27 - Nov 2; Seoul, Korea (South). IEEE; 2019. pp. 1314-24. DOI
               32. Krizhevsky A, Sutskever I, Hinton GE. Imagenet classification with deep convolutional neural networks. Commun ACM 2017;60:84-90.
                  DOI
               33. Devaguptapu C, Akolekar N, Sharma MM, Balasubramanian VN. Borrow from anywhere: pseudo multi-modal object detection in thermal
                  imagery. In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW); 2019 Jun 16-17; Long
                  Beach, CA, USA. IEEE; 2019. pp. 1029-38. DOI
               34. Cao Y, Zhou T, Zhu X, Su Y. Every feature counts: an improved one-stage detector in thermal imagery. In: 2019 IEEE 5th International
                  Conference on Computer and Communications (ICCC); 2019 Dec 6-9; Chengdu, China. IEEE; 2019. pp. 1965-69. DOI
               35. Chen R, Liu S, Mu J, Miao Z, Li F. Borrow from source models: efficient infrared object detection with limited examples. Appl Sci
                  2022;12:1896. DOI
               36. Zha C, Luo S, Xu X. Infrared multi-target detection and tracking in dense urban traffic scenes. IET Image Process 2024;18:1613-28. DOI
               37. Kera SB, Tadepalli A, Ranjani JJ. A paced multi-stage block-wise approach for object detection in thermal images. Vis Comput
                  2023;39:2347-63. DOI
               38. Dong J, Ota K, Dong M. Real-time survivor detection in UAV thermal imagery based on deep learning. In: 2020 16th International
                  Conference on Mobility, Sensing and Networking (MSN); 2020 Dec 17-19; Tokyo, Japan. IEEE; 2020. pp. 352-59. DOI
               39. Ghose D, Desai SM, Bhattacharya S, Chakraborty D, Fiterau M, Rahman T. Pedestrian detection in thermal images using saliency maps.
                  In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW); 2019 Jun 16-17; Long Beach, CA,
                  USA. IEEE; 2019. pp. 988-97. DOI
               40. Dasgupta K, Das A, Das S, Bhattacharya U, Yogamani S. Spatio-contextual deep network-based multimodal pedestrian detection for
                  autonomous driving. IEEE Trans Intell Trans Syst 2022;23:15940-50. DOI
               41. Hsia CH, Peng HC, Chan HT. All-weather pedestrian detection based on double-stream multispectral network. Electronics 2023;12:2312.
                  DOI
               42. Li Y, Li S, Du H, Chen L, Zhang D, Li Y. YOLO-ACN: focusing on small target and occluded object detection. IEEE Access 2020;8:227288-
                  303. DOI
   66   67   68   69   70   71   72   73   74   75   76