참고문헌 (41)

1. Pattern Recognit J Gu 77 354 2018 10.1016/j.patcog.2017.10.013 Gu J, Wang Z, Kuen J, Ma L, Shahroudy A, Shuai B, Chen T (2018) Recent advances in convolutional neural networks. Pattern Recognit 77:354-377 

   상세보기

2. IEEE Signal Process Mag J Han 35 1 84 2018 10.1109/MSP.2017.2749125 Han J, Zhang D, Cheng G, Liu N, Xu D (2018) Advanced deep-learning techniques for salient and category-specific object detection: a survey. IEEE Signal Process Mag 35(1):84-100 

   상세보기

3. Viola PA, Jones MJ (2001) Rapid object detection using a boosted cascade of simple features. In: CVPR 2001. Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition, IEEE 

4. Int J Comput Vis DG Lowe 60 2 91 2004 10.1023/B:VISI.0000029664.99615.94 Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91-110 

   상세보기

5. IPSJ Trans Comput Vis Appl T Watanabe 2 39 2010 10.2197/ipsjtcva.2.39 Watanabe T, Ito S, Yokoi K (2010) Co-occurrence histograms of oriented gradients for human detection. IPSJ Trans Comput Vis Appl 2:39-47 

   상세보기

6. Pedro FF, David AM, Deva R (2008) A discriminatively trained, multiscale, deformable part model. In: Conference: 2008 IEEE computer society conference on computer vision and pattern recognition (CVPR 2008), 24-26 June 2008, IEEE, Anchorage, Alaska, USA 

7. 10.1109/CVPR.2014.81 Girshick R, Donahue J, Darrell T, Malik J (2014) Rich feature hierarchies for accurate object detection and semantic segmentation. In: 2014 IEEE conference on computer vision and pattern recognition, Columbus, OH, pp. 580-587. https://doi.org/10.1109/CVPR.2014.81 

   

8. IEEE Trans Pattern Anal Mach Intell H Kaiming 37 1904 2015 10.1109/TPAMI.2015.2389824 Kaiming H, Xiangyu Z, Shaoqing R (2015) Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans Pattern Anal Mach Intell 37:1904 

   상세보기

9. IEEE Trans Multimedia J Li 4 1 2015 10.1109/MMUL.2015.22 Li J, Liang X, Shen S, Xu T, Feng J, Yan S (2015) Scale-aware fast r-cnn for pedestrian detection. IEEE Trans Multimedia 4:1-1 

   상세보기

10. IEEE Trans Image Process W Wang 27 1 38 2017 10.1109/TIP.2017.2754941 Wang W, Shen J, Shao L (2017) Video salient object detection via fully convolutional networks. IEEE Trans Image Process 27(1):38-49 

    상세보기

11. Ken L, Jiaojiao HE, Yongping Z (2019) Improved tiny-yolo vehicle detection algorithm. In: Computer digital engineering 

12. 10.1007/978-3-030-58309-5_17 Hussain N, Finelli C (2020) KP-YOLO: a modification of YOLO algorithm for the keypoint-based detection of QR codes. In: Artificial neural networks in pattern recognition 

    

13. Jiachen Z, Qingkui C (2019) Road vehicle congestion analysis model based on YOLO. J Comput Appl 

14. 10.1088/1757-899X/563/4/042027 Zhou L, Wei S, Cui Z (2019) YOLO-RD: a lightweight object detection network for range doppler radar images. In: IOP conference series materials science and engineering, vol 563, p 042027 

    상세보기

15. 10.1109/CVPR.2018.00913 Liu S, Qi L, Qin H (2018) path aggregation network for instance segmentation. In: CVF conference on computer vision and pattern recognition (CVPR), IEEE 

    

16. 10.1109/ICCV.2017.322 He K, Gkioxari G, Piotr D (2017) Mask R-CNN. In: IEEE international conference on computer vision (ICCV), IEEE 

    

17. 10.15353/vsnl.v3i1.171 Shafiee MJ, Chywl B, Li F (2017) Fast YOLO: a fast you only look once system for real-time embedded object detection in video. J Comput Vis Imaging Syst 3(1) 

    

18. 10.1109/CVPR.2016.91 Redmon J, Divvala S, Girshick R (2016) You only look once: unified, real-time object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 779-788 

    

19. IEEE Access C Chaoxia 99 1 2020 Chaoxia C, Shang W, Zhang F (2020) Information-guided flame detection based on faster r-cnn. IEEE Access 99:1-1 

20. 10.1007/978-3-319-46448-0_2 Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu CY, Berg AC (2016) Ssd: single shot multibox detector. In: European conference on computer vision, Springer, pp 21-37 

    

21. IEEE Trans Pattern Anal Mach Intell S Ren 39 6 1137 2017 10.1109/TPAMI.2016.2577031 Ren S, He K, Girshick R, Sun J (2017) Faster r-cnn: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137-1149 

    상세보기

22. J Mol Gr Model M Jiang 93 107454 2019 10.1016/j.jmgm.2019.107454 Jiang M, Wei Z, Zhang S, Wang S, Li Z (2019) Frsite: protein drug binding site prediction based on faster r-cnn. J Mol Gr Model 93:107454 

    상세보기

23. Appl Intell H Xie 49 3 1200 2019 10.1007/s10489-018-1326-8 Xie H, Chen Y, Shin H (2019) Context-aware pedestrian detection especially for small-sized instances with deconvolution integrated faster rcnn (dif r-cnn). Appl Intell 49(3):1200-1211 

    상세보기

24. Math Probl Eng H Nguyen 2019 3 1 2019 Nguyen H (2019) Improving faster r-cnn framework for fast vehicle detection. Math Probl Eng 2019(3):1-11 

25. Electr Eng T Lin 103 1 2020 Lin T, Liu X (2020) An intelligent recognition system for insulator string defects based on dimension correction and optimized faster r-cnn. Electr Eng 103:1-9 

26. IEEE Signal Process Lett Z Wang 9 5 160 2002 10.1109/LSP.2002.1009009 Wang Z, Bovik AC (2002) Bitplane-by-bitplane shift (bbbshift)-a suggestion for jpeg2000 region of interest image coding. IEEE Signal Process Lett 9(5):160-162 

    상세보기

27. 10.1109/ICCV.2019.00140 Howard A, Sandler M, Chen B, Wang W, Chen LC, Tan M (2019) Searching for MobileNetV3. In: CVF international conference on computer vision (ICCV), IEEE 

    

28. 10.1109/ICASSP40776.2020.9054428 Chu X, Zhang B, Xu R (2020) MoGA: searching beyond Mobilenetv3. In: ICASSP 2020-2020 IEEE international conference on acoustics, speech and signal processing (ICASSP), IEEE 

    

29. IEEE Trans Knowl Data Eng SJ Pan 22 10 1345 2010 10.1109/TKDE.2009.191 Pan SJ, Yang Q (2010) A survey on transfer learning. IEEE Trans Knowl Data Eng 22(10):1345-1359 

    상세보기

30. Comput Intell Mag IEEE V Jayaram 11 1 20 2016 10.1109/MCI.2015.2501545 Jayaram V, Alamgir M, Altun Y, Scholkopf B, Grosse-Wentrup M (2016) Transfer learning in brain-computer interfaces abstractthe performance of brain-computer interfaces (bcis) improves with the amount of avail. Comput Intell Mag IEEE 11(1):20-31 

    상세보기

31. Neurocomputing MM Ghazi 235 228 2017 10.1016/j.neucom.2017.01.018 Ghazi MM, Yanikoglu B, Aptoula E (2017) Plant identification using deep neural networks via optimization of transfer learning parameters. Neurocomputing 235:228-235 

    상세보기

32. Howard AG, Zhu M, Chen B (2017) Mobilenets: efficient convolutional neural networks for mobile vision applications 

33. IEEE Trans Med Imaging L Xiao 99 1 2020 Xiao L, Luo C, Yu T, Luo Y, Qiao J (2020) Deepacev2: automated chromosome enumeration in metaphase cell images using deep convolutional neural networks. IEEE Trans Med Imaging 99:1-1 

34. Inf Sci F Cao 456 34 2018 10.1016/j.ins.2018.05.006 Cao F, Liu Y, Wang D (2018) Efficient saliency detection using convolutional neural networks with feature selection. Inf Sci 456:34-49 

    상세보기

35. Int J Remote Sens E Kilic 40 11 4193 2019 10.1080/01431161.2018.1562260 Kilic E, Ozturk S (2019) A subclass supported convolutional neural network for object detection and localization in remote-sensing images. Int J Remote Sens 40(11):4193-4212 

    상세보기

36. Int J Adv Comput Sci Appl MM Rahman 11 8 309 2020 Rahman MM, Biswas AA, Rajbongshi A, Majumder A (2020) Recognition of local birds of Bangladesh using mobilenet and inception-v3. Int J Adv Comput Sci Appl 11(8):309-316 

37. 10.1109/ICDAR.2019.00135 Huang Y, Yan Q, Li Y (2019) A YOLO-based table detection method. In: International conference on document analysis and recognition (ICDAR), IEEE 

    

38. Alexey B, Chien-Yao W, Hong-Yuan ML (2020) YOLOv4: optimal speed and accuracy of object detection, pp 1-3 

39. IEEE Trans Ultrason Ferroelectr Freq Control S Kazemirad 63 9 1399 2016 10.1109/TUFFC.2016.2583785 Kazemirad S, Bernard S, Hybois S, Tang A, Cloutier G (2016) Ultrasound shear wave viscoelastography: model-independent quantification of the complex shear modulus. IEEE Trans Ultrason Ferroelectr Freq Control 63(9):1399-1408 

    상세보기

40. Comput Mech O Ezvan 59 2 219 2017 10.1007/s00466-016-1348-1 Ezvan O, Batou A, Soize C, Gagliardini L (2017) Multilevel model reduction for uncertainty quantification in computational structural dynamics. Comput Mech 59(2):219-246 

    상세보기

41. Wirel Commun Mob Comput MM Aslam 2021 16 2021 10.1155/2021/7125482 Aslam MM, Du L, Ahmed Z, Irshad MN, Azeem H (2021) A deep learning-based power control and consensus performance of spectrum sharing in the CR network. Wirel Commun Mob Comput 2021:16. https://doi.org/10.1155/2021/7125482 

    상세보기