- Zhang Y, Wu C, Zhang T, Liu Y, Zheng Y. Self-attention guidance and multiscale feature fusion-based UAV image object detection. IEEE Geosci Remote Sens Lett. 2023;20:1–5.
- Akshatha KR, Karunakar AK, Shenoy S, Dhareshwar C V, Johnson DG. Manipal-UAV person detection dataset: A step towards benchmarking dataset and algorithms for small object detection. ISPRS J Photogramm Remote Sens. 2023;195:77–89.
- Zhang H, Shao F, He X, Zhang Z, Cai Y, Bi S. Research on object detection and recognition method for UAV aerial images based on improved YOLOv5. Drones. 2023;7(6):402.
- Li X, Diao W, Mao Y, Gao P, Mao X, Li X, et al. OGMN: Occlusion-guided multi-task network for object detection in UAV images. ISPRS J Photogramm Remote Sens. 2023;199:242–57.
- Lu W, Lan C, Niu C, Liu W, Lyu L, Shi Q, et al. A cnn-transformer hybrid model based on cswin transformer for uav image object detection. IEEE J Sel Top Appl Earth Obs Remote Sens. 2023;16:1211–31.
- Wang K, Fu X, Huang Y, Cao C, Shi G, Zha ZJ. Generalized uav object detection via frequency domain disentanglement. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2023. 1064–73.
- Yu M, Leung H. Small-object detection for UAV-based images. In: 2023 IEEE International Systems Conference (SysCon). IEEE; 2023. 1–6.
- Lu S, Lu H, Dong J, Wu S. Object detection for UAV aerial scenarios based on vectorized IOU. Sensors. 2023;23(6):3061.
- Ye T, Qin W, Zhao Z, Gao X, Deng X, Ouyang Y. Real-time object detection network in UAV-vision based on CNN and transformer. IEEE Trans Instrum Meas. 2023;72:1–13.
- Gallo I, Rehman AU, Dehkordi RH, Landro N, La Grassa R, Boschetti M. Deep object detection of crop weeds: Performance of YOLOv7 on a real case dataset from UAV images. Remote Sens. 2023;15(2):539.
- Tian G, Liu J, Yang W. A dual neural network for object detection in UAV images. Neurocomputing. 2021;443:292–301.
- Zou Z, Chen K, Shi Z, Guo Y, Ye J. Object detection in 20 years: A survey. Proc IEEE. 2023;111(3):257–76.
- Kaur J, Singh W. Tools, techniques, datasets and application areas for object detection in an image: a review. Multimed Tools Appl. 2022;81(27):38297–351.
- Diwan T, Anirudh G, Tembhurne J V. Object detection using YOLO: Challenges, architectural successors, datasets and applications. Multimed Tools Appl. 2023;82(6):9243–75.
- Kaur J, Singh W. A systematic review of object detection from images using deep learning. Multimedia Tools and Applications. 2024 Jan;83(4):12253-338.
- Xiao Y, Tian Z, Yu J, Zhang Y, Liu S, Du S, et al. A review of object detection based on deep learning. Multimed Tools Appl. 2020;79:23729–91.
- Zhao H, Zhang H, Zhao Y. Yolov7-sea: Object detection of maritime uav images based on improved yolov7. In: Proceedings of the IEEE/CVF winter conference on applications of computer vision. 2023. 233–8.
- Zaaboub N, Guebsi R, Chaouachi RS, Brik B, Rotini A, Chiesa S, et al. Using unmanned aerial vehicles (UAVs) and machine learning techniques for the assessment of Posidonia debris and marine (plastic) litter on coastal ecosystems. Reg Stud Mar Sci. 2023;67:103185.
- Masood H, Zafar A, Ali MU, Hussain T, Khan MA, Tariq U, et al. Tracking of a fixed-shape moving object based on the gradient descent method. Sensors. 2022;22(3):1098.
- Nagaraju M, Babu BS, Sai Somayajulu MV, Sarma KSK, Vetagiri A. An accurate foreground moving object detection based on segmentation techniques and optimal classifier. Concurr Comput Pract Exp. 2022;34(5):e6689.
- Charouh Z, Ezzouhri A, Ghogho M, Guennoun Z. A resource-efficient CNN-based method for moving vehicle detection. Sensors. 2022;22(3):1193.
- Dong X, Yan S, Duan C. A lightweight vehicles detection network model based on YOLOv5. Eng Appl Artif Intell. 2022;113:104914.
- Zhang H, Tian M, Shao G, Cheng J, Liu J. Target detection of forward-looking sonar image based on improved YOLOv5. IEEE Access. 2022;10:18023–34.
- Li X, Wang Z, Geng S, Wang L, Zhang H, Liu L, et al. Yolov3-Pruning (transfer): real-time object detection algorithm based on transfer learning. J Real-Time Image Process. 2022;19(4):839–52.
- Domingo JD, Gomez-Garcia-Bermejo J, Zalama E. Improving human activity recognition integrating lstm with different data sources: Features, object detection and skeleton tracking. IEEE Access. 2022;10:68213–30.
- Yang WJ, Liow WJ, Chen SF, Yang JF, Chung PC, Mao S. Improved vehicle detection systems with double-layer LSTM modules. EURASIP J Adv Signal Process. 2022;2022(1):7.
- Yeuseyenka I, Melnikau I, Yemelyanov I. Detection and selection of moving objects in video images based on impulse and recurrent neural networks. J Data Anal Inf Process. 2022;10(2):127–41.
- Putra FAIA, Utaminingrum F, Mahmudy WF. HOG feature extraction and KNN classification for detecting vehicle in the highway. IJCCS (Indonesian J Comput Cybern Syst. 2020;14(3):231–42.
- Sandino J, Vanegas F, Gonzalez F, Maire F. Autonomous uav navigation for active perception of targets in uncertain and cluttered environments. In: 2020 IEEE Aerospace Conference. IEEE; 2020. 1–12.
- Viola P, Jones M. Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition CVPR 2001. Ieee; 2001. I–I.
|
