초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구조 설계

Tayara, Hilal 2019년

활용도
공유도
영향력

논문상세정보

- 저자 Tayara, Hilal
- 기타서명 Design of Deep Learning Architectures for Object Detection in Very High-Resolution Aerial Images
- 형태사항 삽화, 표: xv, 129 p.: 26 cm
- 일반주기 지도교수: 정길도, 전북대학교 논문은 저작권에 의해 보호받습니다, 참고문헌 : p. 110-129
- 학위논문사항 학위논문(박사)-, 전북대학교 일반대학원, 전자·정보공학부(전자공학 전공), 2019. 2
- 발행지 전주
- 언어 eng
- 출판년 2019
- 발행사항 전북대학교 일반대학원
- 주제어 Aerial image convolution neural network deep learning object detection 딥러닝 알고리즘 물체검출 컨벌류션 신경 망 항공 이미지
- 참고문헌( 149)
유사주제 논문( 1,173)

인용/피인용

초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구 ...

' 초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구조 설계' 의 주제별 논문영향력

논문영향력 요약
동일주제 총논문수	논문피인용 총횟수	주제별 논문영향력의 평균
주제	Aerial image convolution neural network deep learning object detection 딥러닝 알고리즘 물체검출 컨벌류션 신경 망 항공 이미지
1,181	0	0.0%

논문영향력
주제		주제별 논문수	주제별 논문영향력
주제어	Aerial image	7	0.0%
	convolution neural network	32	0.0%
	deep learning	952	0.0%
	object detection	163	0.0%
	딥러닝 알고리즘	18	0.0%
	물체검출	7	0.0%
	컨벌류션 신경 망	1	0.0%
	항공 이미지	1	0.0%
계		1,181	0.0%
* 다른 주제어 보유 논문에서 피인용된 횟수

' 초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구조 설계' 의 참고문헌

Zhenyu An, Zhenwei Shi, Xichao Teng, Xinran Yu, and Wei Tang. An automated airplane detection system for large panchromatic image with high spatial resolution. Optik - International Journal for Light and Electron Optics, 125(12):2768 – 2775, 2014.
Zhaozhuo Xu, Xin Xu, Lei Wang, Rui Yang, and Fangling Pu. Deformable convnet with aspect ratio constrained nms for object detection in remote sensing imagery. Remote Sensing, 9(12), 2017.
Z. Zheng, X. Wang, G. Zhou, and L. Jiang. Vehicle detection based on morphology from highway aerial images. In 2012 IEEE International Geoscience and Remote Sensing Symposium, pages 5997–6000, 2012.
Z. Miao, W. Shi, H. Zhang, and X. Wang. Road centerline extraction from high-resolution imagery based on shape features and multivariate adaptive regression splines. IEEE Geoscience and Remote Sensing Letters, 10(3):583–587, May 2013.
Z. Deng, H. Sun, S. Zhou, J. Zhao, and H. Zou. Toward fast and accurate vehicle detection in aerial images using coupled region-based convolutional neural networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(8):3652–3664, 2017.
Z. Chen, C.Wang, C.Wen, X. Teng, Y. Chen, H. Guan, H. Luo, L. Cao, and J. Li. Vehicle detection in high-resolution aerial images via sparse representation and superpixels. IEEE Transactions on Geoscience and Remote Sensing, 54(1):103–116, 2016.
Yu Li, Jonathan Li, and Y Lu. A fuzzy segmentation-based approach to extraction of coastlines from ikonos imagery. Geomatica, 62(4):396– 408, 2008.
Yi Su Hongping Cai. Airplane detection in remote sensing image with a circle-frequency filter, 2006.
Yann LeCun, L eon Bottou, Yoshua Bengio, and Patrick Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278–2324, 1998.
Yann LeCun, Bernhard E Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne E Hubbard, and Lawrence D Jackel. Handwritten digit recognition with a back-propagation network. In Advances in neural information processing systems, pages 396–404, 1990.
Yann LeCun, Bernhard Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne Hubbard, and Lawrence D Jackel. Backpropagation applied to handwritten zip code recognition. Neural computation, 1(4):541–551, 1989.
Y. Yang, Y. Zhuang, F. Bi, H. Shi, and Y. Xie. M-fcn: Effective fully convolutional network-based airplane detection framework. IEEE Geoscience and Remote Sensing Letters, 14(8):1293–1297, Aug 2017.
Y. Xu, G. Yu, Y. Wang, X. Wu, and Y. Ma. A hybrid vehicle detection method based on viola-jones and hog + svm from uav images. Sensors (Basel), 16(8), 2016. Xu, Yongzheng Yu, Guizhen Wang, Yunpeng Wu, Xinkai Ma, Yalong eng Switzerland Basel, Switzerland 2016/08/23 06:00 Sensors (Basel). 2016 Aug 19;16(8). pii: E1325. doi: 10.3390/s16081325.
Y. Long, Y. Gong, Z. Xiao, and Q. Liu. Accurate object localization in remote sensing images based on convolutional neural networks. IEEE Transactions on Geoscience and Remote Sensing, 55(5):2486–2498, May 2017.
Xunxun Zhang, Hongke Xu, Jianwu Fang, and Gang Sheng. Urban vehicle detection in high-resolution aerial images via superpixel segmentation and correlation-based sequential dictionary learning. Journal of Applied Remote Sensing, 11(2):026028–026028, 2017. 10.1117/1.JRS.11.026028.
Xinran Yu and Zhenwei Shi. Vehicle detection in remote sensing imagery based on salient information and local shape feature. Optik - International Journal for Light and Electron Optics, 126(20):2485 – 2490, 2015.
Xiaoying Jin and Curt H Davis. Vehicle detection from high-resolution satellite imagery using morphological shared-weight neural networks. Image and Vision Computing, 25(9):1422–1431, 2007.
X. Wen, L. Shao, W. Fang, and Y. Xue. Efficient feature selection and classification for vehicle detection. IEEE Transactions on Circuits and Systems for Video Technology, 25(3):508–517, March 2015.
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C. Berg. Ssd: Single shot multibox detector. In Bastian Leibe, Jiri Matas, Nicu Sebe, and MaxWelling, editors, Computer Vision – ECCV 2016, pages 21–37, Cham, 2016. Springer International Publishing.
Wei Guo, Wen Yang, Haijian Zhang, and Guang Hua. Geospatial object detection in high resolution satellite images based on multi-scale convolutional neural network. Remote Sensing, 10(1), 2018.
W. Liu, F. Yamazaki, and T. T. Vu. Automated vehicle extraction and speed determination from quickbird satellite images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4(1):75–82, 2011.
Vincent Dumoulin and Francesco Visin. A guide to convolution arithmetic for deep learning. arXiv preprint arXiv:1603.07285, 2016.
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollar. Focal loss for dense object detection. In The IEEE International Conference on Computer Vision (ICCV), Oct 2017.
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll ar, and C. Lawrence Zitnick. Microsoft coco: Common objects in context. In David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars, editors, Computer Vision – ECCV 2014, pages 740–755, Cham, 2014. Springer International Publishing.
Tianyu Tang, Shilin Zhou, Zhipeng Deng, Huanxin Zou, and Lin Lei. Vehicle detection in aerial images based on region convolutional neural networks and hard negative example mining. Sensors, 17(2):336, 2017.
Thomas Moranduzzo, Farid Melgani, Yakoub Bazi, and Naif Alajlan. A fast object detector based on high-order gradients and gaussian process regression for uav images. Int. J. Remote Sens., 36(10):2713–2733, 2015.
Thomas Lillesand, Ralph W Kiefer, and Jonathan Chipman. Remote sensing and image interpretation. John Wiley & Sons, 2014.
Thomas Key, Timothy A Warner, James B McGraw, and Mary Ann Fajvan. A comparison of multispectral and multitemporal information in high spatial resolution imagery for classification of individual tree species in a temperate hardwood forest. Remote Sensing of Environment, 75(1):100–112, 2001.
Tao Qu, Quanyuan Zhang, and Shilei Sun. Vehicle detection from highresolution aerial images using spatial pyramid pooling-based deep convolutional neural networks. Multimedia Tools and Applications, 2016.
T. Moranduzzo and F. Melgani. Detecting cars in uav images with a catalog-based approach. IEEE Transactions on Geoscience and Remote Sensing, 52(10):6356–6367, 2014.
T. Moranduzzo and F. Melgani. Automatic car counting method for unmanned aerial vehicle images. IEEE Transactions on Geoscience and Remote Sensing, 52(3):1635–1647, 2014.
T Tieleman and G. Hinton. Lecture 6.5 - rmsprop. Report, COURSERA: Neural Networks for Machine Learning., 2012.
Stuart Dreyfus. The numerical solution of variational problems. Journal of Mathematical Analysis and Applications, 5(1):30–45, 1962.
Steven R Garrity, Craig D Allen, Steven P Brumby, Chandana Gangodagamage, Nate G McDowell, and D Michael Cai. Quantifying tree mortality in a mixed species woodland using multitemporal high spatial resolution satellite imagery. Remote Sensing of Environment, 129:54– 65, 2013.
Sergey Ioffe and Christian Szegedy. Batch normalization: Accelerating deep network training by reducing internal covariate shift. CoRR, abs/1502.03167, 2015.
Serge Andr efou et, Philip Kramer, Damaris Torres-Pulliza, Karen E Joyce, Eric J Hochberg, Rodrigo Garza-P erez, Peter J Mumby, Bernhard Riegl, Hiroya Yamano, William H White, et al. Multi-site evalua- tion of ikonos data for classification of tropical coral reef environments. Remote sensing of environment, 88(1-2):128–143, 2003.
Seppo Linnainmaa. The representation of the cumulative rounding error of an algorithm as a taylor expansion of the local rounding errors. Master’s Thesis (in Finnish), Univ. Helsinki, pages 6–7, 1970.
Sepp Hochreiter and J urgen Schmidhuber. Feature extraction through lococode. Neural Computation, 11(3):679–714, 1999.
Santhosh K Seelan, Soizik Laguette, Grant M Casady, and George A Seielstad. Remote sensing applications for precision agriculture: A learning community approach. Remote Sensing of Environment, 88(1- 2):157–169, 2003.
Saining Xie, Ross B. Girshick, Piotr Doll ar, Zhuowen Tu, and Kaiming He. Aggregated residual transformations for deep neural networks. CoRR, abs/1611.05431, 2016.
S. Xu, T. Fang, D. Li, and S. Wang. Object classification of aerial images with bag-of-visual words. IEEE Geoscience and Remote Sensing Letters, 7(2):366–370, April 2010.
S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(6):1137–1149, 2017.
S. Maji, A. C. Berg, and J. Malik. Classification using intersection kernel support vector machines is efficient. In 2008 IEEE Conference on Computer Vision and Pattern Recognition, pages 1–8, 2008.
S. Bo and Y. Jing. Region-based airplane detection in remotely sensed imagery. In 2010 3rd International Congress on Image and Signal Processing, volume 4, pages 1923–1926, Oct 2010.
S Stramondo, C Bignami, M Chini, N Pierdicca, and A Tertulliani. Satellite radar and optical remote sensing for earthquake damage detection: results from different case studies. International Journal of Remote Sensing, 27(20):4433–4447, 2006.
Ross Girshick. Fast r-cnn. In Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV), ICCV ’15, pages 1440– 1448, Washington, DC, USA, 2015. IEEE Computer Society.
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2014.
Ronald J Williams and David Zipser. A learning algorithm for continually running fully recurrent neural networks. Neural computation, 1(2):270–280, 1989.
Robert A Schowengerdt. Remote sensing: models and methods for image processing. Elsevier, 2006.
Raul Rojas. Neural networks: a systematic introduction. 2009.
R. Ruskone, L. Guigues, S. Airault, and O. Jamet. Vehicle detection on aerial images: a structural approach. In Proceedings of 13th International Conference on Pattern Recognition, volume 3, pages 900–904 vol.3, 1996.
Piotr Doll ar. Piotr’s Computer Vision Matlab Toolbox (PMT).
Pierre Sermanet, David Eigen, Xiang Zhang, Micha el Mathieu, Rob Fergus, and Yann LeCun. Overfeat: Integrated recognition, localization and detection using convolutional networks. CoRR, abs/1312.6229, 2013.
Peter J Mumby, William Skirving, Alan E Strong, John T Hardy, Ellsworth F LeDrew, Eric J Hochberg, Rick P Stumpf, and Laura T David. Remote sensing of coral reefs and their physical environment. Marine pollution bulletin, 48(3-4):219–228, 2004.
PaulWerbos. Beyond regression:” new tools for prediction and analysis in the behavioral sciences. Ph. D. dissertation, Harvard University, 1974.
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei. Imagenet large scale visual recognition challenge. International Journal of Computer Vision, 115(3):211–252, 2015.
NitishSrivastava,GeoffreyHinton,AlexKrizhevsky,IlyaSutskever,andRuslanSalakhutdinov. Dropout:asimple waytopreventneuralnetworksfrom overfitting.TheJournalofMachineLearningResearch,15(1):1929–1958,2014.
Nicholas C Coops, Matt Johnson, Michael A Wulder, and Joanne C White. Assessment of quickbird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation. Remote Sensing of Environment, 103(1):67–80, 2006.
National Research Council et al. Landsat and Beyond: Sustaining and Enhancing the Nation’s Land Imaging Program. National Academies Press, 2013.
Nassim Ammour, Haikel Alhichri, Yakoub Bazi, Bilel Benjdira, Naif Alajlan, and Mansour Zuair. Deep learning approach for car detection in uav imagery. Remote Sensing, 9(4):312, 2017.
N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), volume 1, pages 886–893 vol. 1, 2005.
Min Lin, Qiang Chen, and Shuicheng Yan. Network in network. CoRR, abs/1312.4400, 2013.
Michael A Wulder, Joanne C White, Samuel N Goward, Jeffrey G Masek, James R Irons, Martin Herold, Warren B Cohen, Thomas R Loveland, and Curtis E Woodcock. Landsat continuity: Issues and opportunities for land cover monitoring. Remote Sensing of Environment, 112(3):955–969, 2008.
Michael A Wulder, Caren C Dymond, Joanne C White, Donald G Leckie, and Allan L Carroll. Surveying mountain pine beetle damage of forests: A review of remote sensing opportunities. Forest Ecology and management, 221(1-3):27–41, 2006.
Matthias S Moeller and Thomas Blaschke. Urban change extraction from high resolution satellite image. In ISPRS Technical Commission II Symposium, pages 12–14. Citeseer, 2006.
M. Kampffmeyer, A. B. Salberg, and R. Jenssen. Semantic segmentation of small objects and modeling of uncertainty in urban remote sensing images using deep convolutional neural networks. In 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 680–688, June 2016.
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results. http://www.pascalnetwork. org/challenges/VOC/voc2012/workshop/index.html.
M. Abadi, P. Barham, J. Chen, Z Chen, A. Davis, J. Dean, M. Devin, S. Ghemawat, G. Irving, M. Isard, M. Kudlur, J. Levenberg, R. Monga, S. Moore, D. G. Murray, B. Steiner, P. Tucker, V. Vasudevan, P. Warden, M. Wicke, Y. Yu, and X. Zheng. Tensorflow: A system for largescale machine learning. Tech. rep., Google Brain, 2016. arXiv preprint., 2016.
Line Eikvil, Lars Aurdal, and Hans Koren. Classification-based vehicle detection in high-resolution satellite images. ISPRS Journal of Photogrammetry and Remote Sensing, 64(1):65–72, 2009.
L.W. Sommer, T. Schuchert, and J. Beyerer. Fast deep vehicle detection in aerial images. In 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), pages 311–319, 2017.
L. Zhang, Z. Shi, and J. Wu. A hierarchical oil tank detector with deep surrounding features for high-resolution optical satellite imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(10):4895–4909, Oct 2015.
L Yann. Modeles connexionnistes de lapprentissage. PhD thesis, PhD thesis, These de Doctorat, Universite Paris 6, 1987.
Kunihiko Fukushima. Neural network model for a mechanism of pattern recognition unaffected by shift in position-neocognitron. IEICE Technical Report, A, 62(10):658–665, 1979.
Karen Simonyan and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. CoRR, abs/1409.1556, 2014.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification, 2015.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016.
Kaiming He, Georgia Gkioxari, Piotr Doll ar, and Ross B. Girshick. Mask R-CNN. CoRR, abs/1703.06870, 2017.
K. Stankov and D. C. He. Detection of buildings in multispectral very high spatial resolution images using the percentage occupancy hit-ormiss transform. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(10):4069–4080, Oct 2014.
K. Liu and G. Mattyus. Fast multiclass vehicle detection on aerial images. IEEE Geoscience and Remote Sensing Letters, 12(9):1938–1942, 2015.
K. Li, G. Cheng, S. Bu, and X. You. Rotation-insensitive and contextaugmented object detection in remote sensing images. IEEE Trans- actions on Geoscience and Remote Sensing, 56(4):2337–2348, April 2018.
Junwei Han, Peicheng Zhou, Dingwen Zhang, Gong Cheng, Lei Guo, Zhenbao Liu, Shuhui Bu, and Jun Wu. Efficient, simultaneous detection of multi-class geospatial targets based on visual saliency modeling and discriminative learning of sparse coding. ISPRS Journal of Photogrammetry and Remote Sensing, 89:37 – 48, 2014.
Juan B Mena. State of the art on automatic road extraction for gis update: a novel classification. Pattern recognition letters, 24(16):3037– 3058, 2003.
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi. You only look once: Unified, real-time object detection. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016.
Jonathan Masci, Ueli Meier, Gabriel Fricout, and Jurgen Schmidhuber. Multi-scale pyramidal pooling network for generic steel defect classification. In Neural Networks (IJCNN), The 2013 International Joint Conference on, pages 1–8. IEEE, 2013.
Jonathan Masci, Alessandro Giusti, Dan Cires an, Gabriel Fricout, and J urgen Schmidhuber. A fast learning algorithm for image segmentation with max-pooling convolutional networks. arXiv preprint arXiv:1302.1690, 2013.
Jim Thomas, Ahsan Kareem, and Kevin W Bowyer. Automated poststorm damage classification of low-rise building roofing systems using high-resolution aerial imagery. IEEE Transactions on Geoscience and Remote Sensing, 52(7):3851–3861, 2014.
Jifeng Dai, Yi Li, Kaiming He, and Jian Sun. R-FCN: object detection via region-based fully convolutional networks. CoRR, abs/1605.06409, 2016.
J. Zhang, C. Tao, and Z. Zou. An on-road vehicle detection method for high-resolution aerial images based on local and global structure learning. IEEE Geoscience and Remote Sensing Letters, 14(8):1198– 1202, 2017.
J. R. R. Uijlings, K. E. A. van de Sande, T. Gevers, and A.W. M. Smeulders. Selective search for object recognition. International Journal of Computer Vision, 104(2):154–171, Sep 2013.
J. Leitloff, S. Hinz, and U. Stilla. Vehicle detection in very high resolution satellite images of city areas. IEEE Transactions on Geoscience and Remote Sensing, 48(7):2795–2806, 2010.
J. Han, D. Zhang, G. Cheng, L. Guo, and J. Ren. Object detection in optical remote sensing images based on weakly supervised learning and high-level feature learning. IEEE Transactions on Geoscience and Remote Sensing, 53(6):3325–3337, June 2015.
J. D. Wegner, S. Branson, D. Hall, K. Schindler, and P. Perona. Cataloging public objects using aerial and street-level images; urban trees. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 6014–6023, June 2016.
J urgen Schmidhuber. Learning complex, extended sequences using the principle of history compression. Neural Computation, 4(2):234–242, 1992.
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio. Deep learning, volume 1. MIT press Cambridge, 2016.
I. Colomina and P. Molina. Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 92:79 – 97, 2014.
Henry J Kelley. Gradient theory of optimal flight paths. Ars Journal, 30(10):947–954, 1960.
Helmut Grabner, Thuy Thi Nguyen, Barbara Gruber, and Horst Bischof. On-line boosting-based car detection from aerial images. ISPRS Journal of Photogrammetry and Remote Sensing, 63(3):382–396, 2008.
Hans Gaiser, Maarten de Vries, Ashley Williamson, Valeriu Lacatusu, Andr as, Yann Henon, jjiun, Cristian Gratie, Mihai Morariu, Enrico Liscio, Rodrigo Meira de Andrade, Pedro Conceic ˜ao, hannesedvartsen, Wudi Fang, Mike Clark, Iver Jordal, Max Van Sande, Ori226, Pierre D erian, Muhammed Kocabas, srslynow, Guillaume Erhard, Eduardo Ramos, and Diego. fizyr/keras-retinanet 0.3, May 2018.
Hanqiu Xu. Rule-based impervious surface mapping using high spatial resolution imagery. International Journal of Remote Sensing, 34(1):27– 44, 2013.
H. Tayara, K. Gil Soo, and K. T. Chong. Vehicle detection and counting in high-resolution aerial images using convolutional regression neural network. IEEE Access, 6:2220–2230, 2018.
H. Sun, X. Sun, H. Wang, Y. Li, and X. Li. Automatic target detection in high-resolution remote sensing images using spatial sparse coding bag-of-words model. IEEE Geoscience and Remote Sensing Letters, 9(1):109–113, Jan 2012.
H Liu and KC Jezek. Automated extraction of coastline from satellite imagery by integrating canny edge detection and locally adaptive thresholding methods. International journal of remote sensing, 25(5):937–958, 2004.
Gong Cheng, Junwei Han, Peicheng Zhou, and Lei Guo. Multi-class geospatial object detection and geographic image classification based on collection of part detectors. ISPRS Journal of Photogrammetry and Remote Sensing, 98:119 – 132, 2014.
Gong Cheng and Junwei Han. A survey on object detection in optical remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 117:11 – 28, 2016.
George H Mitri and Ioannis Z Gitas. Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery. International Journal of Applied Earth Observation and Geoinformation, 20:60–66, 2013.
Gabriel B Senay, John G Lyon, Andy DWard, Sue E Nokes, et al. Using high spatial resolution multispectral data to classify corn and soybean crops. Photogrammetric engineering and remote sensing, 66(3):319– 328, 2000.
G. Jun and J. Ghosh. Semisupervised learning of hyperspectral data with unknown land-cover classes. IEEE Transactions on Geoscience and Remote Sensing, 51(1):273–282, Jan 2013.
G. Cheng, P. Zhou, and J. Han. Learning rotation-invariant convolutional neural networks for object detection in vhr optical remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 54(12):7405–7415, Dec 2016.
G. Cheng, J. Han, P. Zhou, and L. Guo. Scalable multi-class geospatial object detection in high-spatial-resolution remote sensing images. In 2014 IEEE Geoscience and Remote Sensing Symposium, pages 2479– 2482, July 2014.
G Doxani, Konstantinos Karantzalos, and Maria Tsakiri-Strati. Monitoring urban changes based on scale-space filtering and object-oriented classification. International Journal of Applied Earth Observation and Geoinformation, 15:38–48, 2012.
Frank Rosenblatt. The perceptron, a perceiving and recognizing automaton Project Para. Cornell Aeronautical Laboratory, 1957.
F. Zhang, B. Du, L. Zhang, and M. Xu. Weakly supervised learning based on coupled convolutional neural networks for aircraft detection. IEEE Transactions on Geoscience and Remote Sensing, 54(9):5553– 5563, Sept 2016.
F. Tanner, B. Colder, C. Pullen, D. Heagy, M. Eppolito, V. Carlan, C. Oertel, and P. Sallee. overhead imagery research data set an annotated data library and tools to aid in the development of computer vision algorithms. In 2009 IEEE Applied Imagery Pattern Recognition Workshop (AIPR 2009), pages 1–8, 2009.
E.C. Barrett. Introduction to Environmental Remote Sensing. Routledge, Abingdon, UK, 2003.
Dominik Brunner, Guido Lemoine, and Lorenzo Bruzzone. Earthquake damage assessment of buildings using vhr optical and sar imagery. IEEE Transactions on Geoscience and Remote Sensing, 48(5):2403– 2420, 2010.
David H Hubel and Torsten N Wiesel. Receptive fields and functional architecture of monkey striate cortex. The Journal of physiology, 195(1):215–243, 1968.
David G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91–110, 2004.
David E Rumelhart, Geoffrey E Hinton, and Ronald JWilliams. Learning internal representations by error propagation. Technical report, California Univ San Diego La Jolla Inst for Cognitive Science, 1985.
Dan Claudiu Ciresan, Ueli Meier, Luca Maria Gambardella, and Jurgen Schmidhuber. Convolutional neural network committees for handwritten character classification. In Document Analysis and Recognition (ICDAR), 2011 International Conference on, pages 1135–1139. IEEE, 2011.
Dan Cires an, Ueli Meier, and J urgen Schmidhuber. Multi-column deep neural networks for image classification. arXiv preprint arXiv:1202.2745, 2012.
Dan Cires an, Ueli Meier, Jonathan Masci, and J urgen Schmidhuber. A committee of neural networks for traffic sign classification. In Neural Networks (IJCNN), The 2011 International Joint Conference on, pages 1918–1921. IEEE, 2011.
Dan C Ciresan, Ueli Meier, Jonathan Masci, Luca Maria Gambardella, and J urgen Schmidhuber. Flexible, high performance convolutional neural networks for image classification. In IJCAI Proceedings- International Joint Conference on Artificial Intelligence, volume 22, page 1237. Barcelona, Spain, 2011.
D. Zhang, D. Meng, and J. Han. Co-saliency detection via a self-paced multiple-instance learning framework. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(5):865–878, May 2017.
D. Dai and W. Yang. Satellite image classification via two-layer sparse coding with biased image representation. IEEE Geoscience and Remote Sensing Letters, 8(1):173–176, Jan 2011.
D Ehrlich, T Kemper, X Blaes, and P Soille. Extracting building stock information from optical satellite imagery for mapping earthquake exposure and its vulnerability. Natural hazards, 68(1):79–95, 2013.
Courage Kamusoko. Importance of Remote Sensing and Land Change Modeling for Urbanization Studies, pages 3–10. Springer Singapore, Singapore, 2017.
Christopher M Bishop. Periodic variables. Pattern recognition and machine learning, 1, 2006.
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. Going deeper with convolutions. CoRR, abs/1409.4842, 2014.
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, and Zbigniew Wojna. Rethinking the inception architecture for computer vision. CoRR, abs/1512.00567, 2015.
Christian Szegedy, Sergey Ioffe, and Vincent Vanhoucke. Inceptionv4, inception-resnet and the impact of residual connections on learning. CoRR, abs/1602.07261, 2016.
Chaoyue Chen, Weiguo Gong, Yan Feng Hu, Yongliang Chen, and Yi Steven Ding. Learning oriented region-based convolutional neural networks for building detection in satellite remote sensing images. In The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017.
CJ Van der Sande, SM De Jong, and APJ De Roo. A segmentation and classification approach of ikonos-2 imagery for land cover mapping to assist flood risk and flood damage assessment. International Journal of applied earth observation and geoinformation, 4(3):217–229, 2003.
C. Chen Y. Tian and M. Shah. Cross-view image matching for geolocalization in urban environments. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017.
Bruno A Olshausen and David J Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381(6583):607, 1996.
Brigitte Leblon. Forest wildfire hazard monitoring using remote sensing: A review. Remote Sensing Reviews, 20(1):1–43, 2001.
Beril Sirmacek and Cem Unsalan. Building detection using local gabor features in very high resolution satellite images. In Recent Advances in Space Technologies, 2009. RAST’09. 4th International Conference on, pages 283–286. IEEE, 2009.
B. Sirmacek and C. Unsalan. A probabilistic framework to detect buildings in aerial and satellite images. IEEE Transactions on Geoscience and Remote Sensing, 49(1):211–221, Jan 2011.
B. Salehi, Y. Zhang, and M. Zhong. Automatic moving vehicles information extraction from single-pass worldview-2 imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(1):135–145, 2012.
Arthur E Bryson. A gradient method for optimizing multi-stage allocation processes. In Proc. Harvard Univ. Symposium on digital computers and their applications, volume 72, 1961.
Antonis Katartzis and Hichem Sahli. A stochastic framework for the identification of building rooftops using a single remote sensing image. IEEE Transactions on Geoscience and Remote Sensing, 46(1):259–271, 2008.
Alfredo Canziani, Adam Paszke, and Eugenio Culurciello. An analysis of deep neural network models for practical applications. CoRR, abs/1605.07678, 2016.
Alexandre Carleer and El eonore Wolff. Exploitation of very high resolution satellite data for tree species identification. Photogrammetric Engineering & Remote Sensing, 70(1):135–140, 2004.
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. Imagenet classification with deep convolutional neural networks, 2012.
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks. In F. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems 25, pages 1097–1105. Curran Associates, Inc., 2012.
Alex Graves. Supervised sequence labelling with recurrent neural networks. 2012. PhD thesis, Technische Universit at M unchen, 2008.
Alex Graves, Santiago Fern andez, Faustino Gomez, and J urgen Schmidhuber. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In Proceedings of the 23rd international conference on Machine learning, pages 369– 376. ACM, 2006.
Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton. Speech recognition with deep recurrent neural networks. In Acoustics, speech and signal processing (icassp), 2013 ieee international conference on, pages 6645–6649. IEEE, 2013.
A. O. Ok and E. Bas eski. Circular oil tank detection from panchromatic satellite images: A new automated approach. IEEE Geoscience and Remote Sensing Letters, 12(6):1347–1351, June 2015.
A. Kembhavi, D. Harwood, and L. S. Davis. Vehicle detection using partial least squares. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(6):1250–1265, 2011.

초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구조 설계

유사주제 논문( 1,173)

' 초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구조 설계' 의 주제별 논문영향력

주제별 논문영향력

' 초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구조 설계' 의 참고문헌

' 초고해상도 항공 이미지의 객체 검출을 위한 딥러닝 구조 설계' 의 유사주제( ) 논문