Journal articles on the topic 'Weakly supervised classifier'
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Jager, M., C. Knoll, and F. A. Hamprecht. "Weakly Supervised Learning of a Classifier for Unusual Event Detection." IEEE Transactions on Image Processing 17, no. 9 (September 2008): 1700–1708. http://dx.doi.org/10.1109/tip.2008.2001043.
Full textWang, Mo, Jing Wang, and Li Chen. "Mapping Paddy Rice Using Weakly Supervised Long Short-Term Memory Network with Time Series Sentinel Optical and SAR Images." Agriculture 10, no. 10 (October 19, 2020): 483. http://dx.doi.org/10.3390/agriculture10100483.
Full textLi Min, Song Yu,, Du Weidong, He Yujie, Gou Yao, Wu Zhaoqing, and Lv Yilong. "Strong Representation Learning for Weakly Supervised Object Detection." International Journal of Engineering and Computer Science 11, no. 02 (February 1, 2022): 25493–507. http://dx.doi.org/10.18535/ijecs/v11i02.4650.
Full textHsu, Kuang-Jui, Yen-Yu Lin, and Yung-Yu Chuang. "Weakly Supervised Salient Object Detection by Learning A Classifier-Driven Map Generator." IEEE Transactions on Image Processing 28, no. 11 (November 2019): 5435–49. http://dx.doi.org/10.1109/tip.2019.2917224.
Full textChoqueluque-Roman, David, and Guillermo Camara-Chavez. "Weakly Supervised Violence Detection in Surveillance Video." Sensors 22, no. 12 (June 14, 2022): 4502. http://dx.doi.org/10.3390/s22124502.
Full textWang, Jue, Ke Chen, Lidan Shou, Sai Wu, and Gang Chen. "Effective Slot Filling via Weakly-Supervised Dual-Model Learning." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 16 (May 18, 2021): 13952–60. http://dx.doi.org/10.1609/aaai.v35i16.17643.
Full textKim, Beomyoung, Sangeun Han, and Junmo Kim. "Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 2 (May 18, 2021): 1754–61. http://dx.doi.org/10.1609/aaai.v35i2.16269.
Full textTai, Chang-Yu, Ming-Yao Li, and Lun-Wei Ku. "Hyperbolic Disentangled Representation for Fine-Grained Aspect Extraction." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (June 28, 2022): 11358–66. http://dx.doi.org/10.1609/aaai.v36i10.21387.
Full textSun, Hao, Xuyun Fu, and Shisheng Zhong. "A Weakly Supervised Gas-Path Anomaly Detection Method for Civil Aero-Engines Based on Mapping Relationship Mining of Gas-Path Parameters and Improved Density Peak Clustering." Sensors 21, no. 13 (July 1, 2021): 4526. http://dx.doi.org/10.3390/s21134526.
Full textGuinard, S., and L. Landrieu. "WEAKLY SUPERVISED SEGMENTATION-AIDED CLASSIFICATION OF URBAN SCENES FROM 3D LIDAR POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 151–57. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-151-2017.
Full textShen, Yiqiu, Nan Wu, Jason Phang, Jungkyu Park, Kangning Liu, Sudarshini Tyagi, Laura Heacock, et al. "An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization." Medical Image Analysis 68 (February 2021): 101908. http://dx.doi.org/10.1016/j.media.2020.101908.
Full textNartey, Obed Tettey, Guowu Yang, Sarpong Kwadwo Asare, Jinzhao Wu, and Lady Nadia Frempong. "Robust Semi-Supervised Traffic Sign Recognition via Self-Training and Weakly-Supervised Learning." Sensors 20, no. 9 (May 8, 2020): 2684. http://dx.doi.org/10.3390/s20092684.
Full textCholakkal, Hisham, Jubin Johnson, and Deepu Rajan. "Backtracking Spatial Pyramid Pooling-Based Image Classifier for Weakly Supervised Top–Down Salient Object Detection." IEEE Transactions on Image Processing 27, no. 12 (December 2018): 6064–78. http://dx.doi.org/10.1109/tip.2018.2864891.
Full textWang, Sherrie, William Chen, Sang Michael Xie, George Azzari, and David B. Lobell. "Weakly Supervised Deep Learning for Segmentation of Remote Sensing Imagery." Remote Sensing 12, no. 2 (January 7, 2020): 207. http://dx.doi.org/10.3390/rs12020207.
Full textGuha, Satarupa, Tanmoy Chakraborty, Samik Datta, Mohit Kumar, and Vasudeva Varma. "TweetGrep: Weakly Supervised Joint Retrieval and Sentiment Analysis of Topical Tweets." Proceedings of the International AAAI Conference on Web and Social Media 10, no. 1 (August 4, 2021): 161–70. http://dx.doi.org/10.1609/icwsm.v10i1.14719.
Full textPark, Nojin, and Hanseok Ko. "Weakly Supervised Learning for Object Localization Based on an Attention Mechanism." Applied Sciences 11, no. 22 (November 19, 2021): 10953. http://dx.doi.org/10.3390/app112210953.
Full textBanerjee, Imon, Kevin Li, Martin Seneviratne, Michelle Ferrari, Tina Seto, James D. Brooks, Daniel L. Rubin, and Tina Hernandez-Boussard. "Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment." JAMIA Open 2, no. 1 (January 4, 2019): 150–59. http://dx.doi.org/10.1093/jamiaopen/ooy057.
Full textLee, Seokjin, Minhan Kim, Seunghyeon Shin, Sooyoung Park, and Youngho Jeong. "Data-Dependent Feature Extraction Method Based on Non-Negative Matrix Factorization for Weakly Supervised Domestic Sound Event Detection." Applied Sciences 11, no. 3 (January 24, 2021): 1040. http://dx.doi.org/10.3390/app11031040.
Full textZhang, Wei, Ping Tang, Thomas Corpetti, and Lijun Zhao. "WTS: A Weakly towards Strongly Supervised Learning Framework for Remote Sensing Land Cover Classification Using Segmentation Models." Remote Sensing 13, no. 3 (January 23, 2021): 394. http://dx.doi.org/10.3390/rs13030394.
Full textAmyar, Amine, Romain Modzelewski, Pierre Vera, Vincent Morard, and Su Ruan. "Weakly Supervised Tumor Detection in PET Using Class Response for Treatment Outcome Prediction." Journal of Imaging 8, no. 5 (May 9, 2022): 130. http://dx.doi.org/10.3390/jimaging8050130.
Full textMirroshandel, S. A., and G. Ghassem-Sani. "Towards Unsupervised Learning of Temporal Relations between Events." Journal of Artificial Intelligence Research 45 (September 26, 2012): 125–63. http://dx.doi.org/10.1613/jair.3693.
Full textDvořák, J., M. Potůčková, and V. Treml. "WEAKLY SUPERVISED LEARNING FOR TREELINE ECOTONE CLASSIFICATION BASED ON AERIAL ORTHOIMAGES AND AN ANCILLARY DSM." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022 (May 17, 2022): 33–38. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-33-2022.
Full textNashaat, Mona, Aindrila Ghosh, James Miller, and Shaikh Quader. "Semi-Supervised Ensemble Learning for Dealing with Inaccurate and Incomplete Supervision." ACM Transactions on Knowledge Discovery from Data 16, no. 3 (June 30, 2022): 1–33. http://dx.doi.org/10.1145/3473910.
Full textGong, Yanwen, Shushrruth Sai Srinivasan, Ruiyi Zhang, Kai Kessenbrock, and Jing Zhang. "scEpiLock: A Weakly Supervised Learning Framework for cis-Regulatory Element Localization and Variant Impact Quantification for Single-Cell Epigenetic Data." Biomolecules 12, no. 7 (June 23, 2022): 874. http://dx.doi.org/10.3390/biom12070874.
Full textPirovano, Antoine, Leandro G. Almeida, Said Ladjal, Isabelle Bloch, and Sylvain Berlemont. "Computer-aided diagnosis tool for cervical cancer screening with weakly supervised localization and detection of abnormalities using adaptable and explainable classifier." Medical Image Analysis 73 (October 2021): 102167. http://dx.doi.org/10.1016/j.media.2021.102167.
Full textMd Ali, Mohd Adli, Nu’man Badrud’din, Hafidzul Abdullah, and Faiz Kemi. "Alternate methods for anomaly detection in high-energy physics via semi-supervised learning." International Journal of Modern Physics A 35, no. 23 (August 12, 2020): 2050131. http://dx.doi.org/10.1142/s0217751x20501316.
Full textSakai, Tomoya, Gang Niu, and Masashi Sugiyama. "Information-Theoretic Representation Learning for Positive-Unlabeled Classification." Neural Computation 33, no. 1 (January 2021): 244–68. http://dx.doi.org/10.1162/neco_a_01337.
Full textNiu, Tong, and Mohit Bansal. "Polite Dialogue Generation Without Parallel Data." Transactions of the Association for Computational Linguistics 6 (December 2018): 373–89. http://dx.doi.org/10.1162/tacl_a_00027.
Full textChoi, Hyun-Tae, and Byung-Woo Hong. "Unsupervised Object Segmentation Based on Bi-Partitioning Image Model Integrated with Classification." Electronics 10, no. 18 (September 18, 2021): 2296. http://dx.doi.org/10.3390/electronics10182296.
Full textChen, Zhanlin, Jing Zhang, Jason Liu, Yi Dai, Donghoon Lee, Martin Renqiang Min, Min Xu, and Mark Gerstein. "DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays." Bioinformatics 37, Supplement_1 (July 1, 2021): i280—i288. http://dx.doi.org/10.1093/bioinformatics/btab283.
Full textPappas, Nikolaos, and Andrei Popescu-Belis. "Explicit Document Modeling through Weighted Multiple-Instance Learning." Journal of Artificial Intelligence Research 58 (March 22, 2017): 591–626. http://dx.doi.org/10.1613/jair.5240.
Full textBazazian, Dena, and M. Eulàlia Parés. "EDC-Net: Edge Detection Capsule Network for 3D Point Clouds." Applied Sciences 11, no. 4 (February 19, 2021): 1833. http://dx.doi.org/10.3390/app11041833.
Full textPan, Bin, Jianhao Tai, Qi Zheng, and Shanshan Zhao. "Cascade Convolutional Neural Network Based on Transfer-Learning for Aircraft Detection on High-Resolution Remote Sensing Images." Journal of Sensors 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/1796728.
Full textKazllarof, Vangjel, Stamatis Karlos, and Sotiris Kotsiantis. "Investigation of Combining Logitboost(M5P) under Active Learning Classification Tasks." Informatics 7, no. 4 (November 3, 2020): 50. http://dx.doi.org/10.3390/informatics7040050.
Full textArachie, Chidubem, and Bert Huang. "Adversarial Label Learning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3183–90. http://dx.doi.org/10.1609/aaai.v33i01.33013183.
Full textXu, Yumo, and Mirella Lapata. "Weakly Supervised Domain Detection." Transactions of the Association for Computational Linguistics 7 (November 2019): 581–96. http://dx.doi.org/10.1162/tacl_a_00287.
Full textYao, Wenlin, Cheng Zhang, Shiva Saravanan, Ruihong Huang, and Ali Mostafavi. "Weakly-Supervised Fine-Grained Event Recognition on Social Media Texts for Disaster Management." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (April 3, 2020): 532–39. http://dx.doi.org/10.1609/aaai.v34i01.5391.
Full textLu, Zheng, and Dali Chen. "Weakly Supervised and Semi-Supervised Semantic Segmentation for Optic Disc of Fundus Image." Symmetry 12, no. 1 (January 10, 2020): 145. http://dx.doi.org/10.3390/sym12010145.
Full textDau, Hoan Manh, Ning Xu, and Tung Khac Truong. "A Survey of Using Weakly Supervised and Semi-Supervised for Cross-Domain Sentiment Classification." Advanced Materials Research 905 (April 2014): 637–41. http://dx.doi.org/10.4028/www.scientific.net/amr.905.637.
Full textBolshina, Angelina Sergeevna, and Natalia Valentinovna Loukachevitch. "Weakly Supervised Word Sense Disambiguation Using Automatically Labelled Collections." Proceedings of the Institute for System Programming of the RAS 33, no. 6 (2021): 193–204. http://dx.doi.org/10.15514/ispras-2021-33(6)-13.
Full textWolf, Daniel, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, and Michael Götz. "Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation." Applied Sciences 12, no. 21 (October 24, 2022): 10763. http://dx.doi.org/10.3390/app122110763.
Full textWolf, Daniel, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, and Michael Götz. "Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation." Applied Sciences 12, no. 21 (October 24, 2022): 10763. http://dx.doi.org/10.3390/app122110763.
Full textWolf, Daniel, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, and Michael Götz. "Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation." Applied Sciences 12, no. 21 (October 24, 2022): 10763. http://dx.doi.org/10.3390/app122110763.
Full textWolf, Daniel, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, and Michael Götz. "Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation." Applied Sciences 12, no. 21 (October 24, 2022): 10763. http://dx.doi.org/10.3390/app122110763.
Full textWolf, Daniel, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, and Michael Götz. "Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation." Applied Sciences 12, no. 21 (October 24, 2022): 10763. http://dx.doi.org/10.3390/app122110763.
Full textWolf, Daniel, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, and Michael Götz. "Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation." Applied Sciences 12, no. 21 (October 24, 2022): 10763. http://dx.doi.org/10.3390/app122110763.
Full textWolf, Daniel, Sebastian Regnery, Rafal Tarnawski, Barbara Bobek-Billewicz, Joanna Polańska, and Michael Götz. "Weakly Supervised Learning with Positive and Unlabeled Data for Automatic Brain Tumor Segmentation." Applied Sciences 12, no. 21 (October 24, 2022): 10763. http://dx.doi.org/10.3390/app122110763.
Full textYun, JooYeol, JungWoo Oh, and IlDong Yun. "Gradually Applying Weakly Supervised and Active Learning for Mass Detection in Breast Ultrasound Images." Applied Sciences 10, no. 13 (June 29, 2020): 4519. http://dx.doi.org/10.3390/app10134519.
Full textCao, Zhiyi, Shaozhang Niu, and Jiwei Zhang. "Weakly Supervised GAN for Image-to-Image Translation in the Wild." Mathematical Problems in Engineering 2020 (March 9, 2020): 1–8. http://dx.doi.org/10.1155/2020/6216048.
Full textCai, Yingfeng, Youguo He, Hai Wang, Xiaoqiang Sun, Long Chen, and Haobin Jiang. "Pedestrian detection algorithm in traffic scene based on weakly supervised hierarchical deep model." International Journal of Advanced Robotic Systems 14, no. 1 (February 14, 2016): 172988141769231. http://dx.doi.org/10.1177/1729881417692311.
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