Academic literature on the topic 'Pixel labeling problems'
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Journal articles on the topic "Pixel labeling problems"
Jung, Ho Yub, Kyoung Mu Lee, and Sang Uk Lee. "Window annealing for pixel-labeling problems." Computer Vision and Image Understanding 117, no. 3 (March 2013): 289–303. http://dx.doi.org/10.1016/j.cviu.2012.12.005.
Full textShao, Zhenfeng, Ke Yang, and Weixun Zhou. "Performance Evaluation of Single-Label and Multi-Label Remote Sensing Image Retrieval Using a Dense Labeling Dataset." Remote Sensing 10, no. 6 (June 16, 2018): 964. http://dx.doi.org/10.3390/rs10060964.
Full textShao, Zhenfeng, Ke Yang, and Weixun Zhou. "Correction: Shao, Z.; et al. A Benchmark Dataset for Performance Evaluation of Multi-Label Remote Sensing Image Retrieval. Remote Sens. 2018, 10, 964." Remote Sensing 10, no. 8 (August 3, 2018): 1220. http://dx.doi.org/10.3390/rs10081220.
Full textMacville, Merryn V. E., Jeroen A. W. M. Van der Laak, Ernst J. M. Speel, Nir Katzir, Yuval Garini, Dirk Soenksen, George McNamara, et al. "Spectral Imaging of Multi-Color Chromogenic Dyes in Pathological Specimens." Analytical Cellular Pathology 22, no. 3 (2001): 133–42. http://dx.doi.org/10.1155/2001/740909.
Full textChen, Linwei, Ying Fu, Shaodi You, and Hongzhe Liu. "Efficient Hybrid Supervision for Instance Segmentation in Aerial Images." Remote Sensing 13, no. 2 (January 13, 2021): 252. http://dx.doi.org/10.3390/rs13020252.
Full textChen, Dali, Yingying Ao, and Shixin Liu. "Semi-Supervised Learning Method of U-Net Deep Learning Network for Blood Vessel Segmentation in Retinal Images." Symmetry 12, no. 7 (June 29, 2020): 1067. http://dx.doi.org/10.3390/sym12071067.
Full textSosnovik, Ivan, and Ivan Oseledets. "Neural networks for topology optimization." Russian Journal of Numerical Analysis and Mathematical Modelling 34, no. 4 (August 27, 2019): 215–23. http://dx.doi.org/10.1515/rnam-2019-0018.
Full textTymchenko, Borys Igorovych. "NEURAL NETWORK METHODS FOR PLANAR IMAGE ANALYSIS IN AUTOMATED SCREENING SYSTEMS." Applied Aspects of Information Technology 4, no. 1 (April 10, 2021): 71–79. http://dx.doi.org/10.15276/aait.01.2021.6.
Full textLing, Feng, Rajamohan Parthasarathy, Ye Wang, and Sokchoo Ng. "Data Augmentation Technology for Improving the Recognition Accuracy of Target Image." Journal of Networking and Telecommunications 2, no. 3 (October 15, 2020): 58. http://dx.doi.org/10.18282/jnt.v2i3.1265.
Full textSaglam, A., and N. A. Baykan. "A SATELLITE IMAGE CLASSIFICATION APPROACH BY USING ONE DIMENSIONAL DISCRIMINANT ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W4 (March 6, 2018): 429–35. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w4-429-2018.
Full textDissertations / Theses on the topic "Pixel labeling problems"
Park, Kyoungup. "A learning framework for higher-order consistency models in multi-class pixel labeling problems." Phd thesis, 2014. http://hdl.handle.net/1885/12686.
Full textBook chapters on the topic "Pixel labeling problems"
An, Lin, Ming Li, Mohamed El Yazid Boudaren, and Wojciech Pieczynski. "Evidential Correlated Gaussian Mixture Markov Model for Pixel Labeling Problem." In Belief Functions: Theory and Applications, 203–11. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45559-4_21.
Full textConference papers on the topic "Pixel labeling problems"
Parthasarathy, G., and P. Ananth Raj. "A unified random field model based neural approach to pixel labeling problems in computer vision." In Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94). IEEE, 1994. http://dx.doi.org/10.1109/icnn.1994.374871.
Full textSun, Tiezhu, Wei Zhang, Zhijie Wang, Lin Ma, and Zequn Jie. "Image-level to Pixel-wise Labeling: From Theory to Practice." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/129.
Full textHabeeb, Haroun, Ankit Anand, Mausam, and Parag Singla. "Coarse-to-Fine Lifted MAP Inference in Computer Vision." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/641.
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