Journal articles on the topic 'Fully- and weakly-Supervised learning'
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Cuypers, Suzanna, Maarten Bassier, and Maarten Vergauwen. "Deep Learning on Construction Sites: A Case Study of Sparse Data Learning Techniques for Rebar Segmentation." Sensors 21, no. 16 (August 11, 2021): 5428. http://dx.doi.org/10.3390/s21165428.
Full textWang, Ning, Jiajun Deng, and Mingbo Jia. "Cycle-Consistency Learning for Captioning and Grounding." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 6 (March 24, 2024): 5535–43. http://dx.doi.org/10.1609/aaai.v38i6.28363.
Full textWang, Guangyao. "A Study of Object Detection Based on Weakly Supervised Learning." International Journal of Computer Science and Information Technology 2, no. 1 (March 25, 2024): 476–78. http://dx.doi.org/10.62051/ijcsit.v2n1.50.
Full textAdke, Shrinidhi, Changying Li, Khaled M. Rasheed, and Frederick W. Maier. "Supervised and Weakly Supervised Deep Learning for Segmentation and Counting of Cotton Bolls Using Proximal Imagery." Sensors 22, no. 10 (May 12, 2022): 3688. http://dx.doi.org/10.3390/s22103688.
Full textNi, Ansong, Pengcheng Yin, and Graham Neubig. "Merging Weak and Active Supervision for Semantic Parsing." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 8536–43. http://dx.doi.org/10.1609/aaai.v34i05.6375.
Full textColin, Aurélien, Ronan Fablet, Pierre Tandeo, Romain Husson, Charles Peureux, Nicolas Longépé, and Alexis Mouche. "Semantic Segmentation of Metoceanic Processes Using SAR Observations and Deep Learning." Remote Sensing 14, no. 4 (February 11, 2022): 851. http://dx.doi.org/10.3390/rs14040851.
Full textCai, Tingting, Hongping Yan, Kun Ding, Yan Zhang, and Yueyue Zhou. "WSPolyp-SAM: Weakly Supervised and Self-Guided Fine-Tuning of SAM for Colonoscopy Polyp Segmentation." Applied Sciences 14, no. 12 (June 8, 2024): 5007. http://dx.doi.org/10.3390/app14125007.
Full textHong, Yining, Qing Li, Daniel Ciao, Siyuan Huang, and Song-Chun Zhu. "Learning by Fixing: Solving Math Word Problems with Weak Supervision." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 6 (May 18, 2021): 4959–67. http://dx.doi.org/10.1609/aaai.v35i6.16629.
Full textChen, Shaolong, and Zhiyong Zhang. "A Semi-Automatic Magnetic Resonance Imaging Annotation Algorithm Based on Semi-Weakly Supervised Learning." Sensors 24, no. 12 (June 16, 2024): 3893. http://dx.doi.org/10.3390/s24123893.
Full textZhang, Yachao, Zonghao Li, Yuan Xie, Yanyun Qu, Cuihua Li, and Tao Mei. "Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (May 18, 2021): 3421–29. http://dx.doi.org/10.1609/aaai.v35i4.16455.
Full textQian, Xiaoliang, Chenyang Lin, Zhiwu Chen, and Wei Wang. "SAM-Induced Pseudo Fully Supervised Learning for Weakly Supervised Object Detection in Remote Sensing Images." Remote Sensing 16, no. 9 (April 26, 2024): 1532. http://dx.doi.org/10.3390/rs16091532.
Full textCherikbayeva, L. Ch, N. K. Mukazhanov, Z. Alibiyeva, S. A. Adilzhanova, G. A. Tyulepberdinova, and M. Zh Sakypbekova. "SOLUTION TO THE PROBLEM WEAKLY CONTROLLED REGRESSION USING COASSOCIATION MATRIX AND REGULARIZATION." Herald of the Kazakh-British technical university 21, no. 2 (July 1, 2024): 83–94. http://dx.doi.org/10.55452/1998-6688-2024-21-2-83-94.
Full textFeng, Jiahao, Ce Li, and Jin Wang. "CAM-TMIL: A Weakly-Supervised Segmentation Framework for Histopathology based on CAMs and MIL." Journal of Physics: Conference Series 2547, no. 1 (July 1, 2023): 012014. http://dx.doi.org/10.1088/1742-6596/2547/1/012014.
Full textChen, Jie, Fen He, Yi Zhang, Geng Sun, and Min Deng. "SPMF-Net: Weakly Supervised Building Segmentation by Combining Superpixel Pooling and Multi-Scale Feature Fusion." Remote Sensing 12, no. 6 (March 24, 2020): 1049. http://dx.doi.org/10.3390/rs12061049.
Full textWu, Zhenyu, Lin Wang, Wei Wang, Qing Xia, Chenglizhao Chen, Aimin Hao, and Shuo Li. "Pixel Is All You Need: Adversarial Trajectory-Ensemble Active Learning for Salient Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 3 (June 26, 2023): 2883–91. http://dx.doi.org/10.1609/aaai.v37i3.25390.
Full textLiu, Xiangquan, and Xiaoming Huang. "Weakly supervised salient object detection via bounding-box annotation and SAM model." Electronic Research Archive 32, no. 3 (2024): 1624–45. http://dx.doi.org/10.3934/era.2024074.
Full textBožič, Jakob, Domen Tabernik, and Danijel Skočaj. "Mixed supervision for surface-defect detection: From weakly to fully supervised learning." Computers in Industry 129 (August 2021): 103459. http://dx.doi.org/10.1016/j.compind.2021.103459.
Full textGe, Yongtao, Qiang Zhou, Xinlong Wang, Chunhua Shen, Zhibin Wang, and Hao Li. "Point-Teaching: Weakly Semi-supervised Object Detection with Point Annotations." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 1 (June 26, 2023): 667–75. http://dx.doi.org/10.1609/aaai.v37i1.25143.
Full textFu, Kun, Wanxuan Lu, Wenhui Diao, Menglong Yan, Hao Sun, Yi Zhang, and Xian Sun. "WSF-NET: Weakly Supervised Feature-Fusion Network for Binary Segmentation in Remote Sensing Image." Remote Sensing 10, no. 12 (December 6, 2018): 1970. http://dx.doi.org/10.3390/rs10121970.
Full textRoth, Holger R., Dong Yang, Ziyue Xu, Xiaosong Wang, and Daguang Xu. "Going to Extremes: Weakly Supervised Medical Image Segmentation." Machine Learning and Knowledge Extraction 3, no. 2 (June 2, 2021): 507–24. http://dx.doi.org/10.3390/make3020026.
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 textWatanabe, Takumi, Hiroki Takahashi, Yusuke Iwasawa, Yutaka Matsuo, and Ikuko Eguchi Yairi. "Weakly Supervised Learning for Evaluating Road Surface Condition from Wheelchair Driving Data." Information 11, no. 1 (December 19, 2019): 2. http://dx.doi.org/10.3390/info11010002.
Full textWang, Lukang, Min Zhang, Xu Gao, and Wenzhong Shi. "Advances and Challenges in Deep Learning-Based Change Detection for Remote Sensing Images: A Review through Various Learning Paradigms." Remote Sensing 16, no. 5 (February 25, 2024): 804. http://dx.doi.org/10.3390/rs16050804.
Full textBaek, Kyungjune, Minhyun Lee, and Hyunjung Shim. "PsyNet: Self-Supervised Approach to Object Localization Using Point Symmetric Transformation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 10451–59. http://dx.doi.org/10.1609/aaai.v34i07.6615.
Full textHoang, Nhat M., Kehong Gong, Chuan Guo, and Michael Bi Mi. "MotionMix: Weakly-Supervised Diffusion for Controllable Motion Generation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (March 24, 2024): 2157–65. http://dx.doi.org/10.1609/aaai.v38i3.27988.
Full textQian, Rui, Yunchao Wei, Honghui Shi, Jiachen Li, Jiaying Liu, and Thomas Huang. "Weakly Supervised Scene Parsing with Point-Based Distance Metric Learning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 8843–50. http://dx.doi.org/10.1609/aaai.v33i01.33018843.
Full textSebai, Meriem, Xinggang Wang, and Tianjiang Wang. "MaskMitosis: a deep learning framework for fully supervised, weakly supervised, and unsupervised mitosis detection in histopathology images." Medical & Biological Engineering & Computing 58, no. 7 (May 22, 2020): 1603–23. http://dx.doi.org/10.1007/s11517-020-02175-z.
Full textLin, Jianghang, Yunhang Shen, Bingquan Wang, Shaohui Lin, Ke Li, and Liujuan Cao. "Weakly Supervised Open-Vocabulary Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 4 (March 24, 2024): 3404–12. http://dx.doi.org/10.1609/aaai.v38i4.28127.
Full textKrishnamurthy, Jayant, and Thomas Kollar. "Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World." Transactions of the Association for Computational Linguistics 1 (December 2013): 193–206. http://dx.doi.org/10.1162/tacl_a_00220.
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 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 textXie, Fei, Panpan Zhang, Tao Jiang, Jiao She, Xuemin Shen, Pengfei Xu, Wei Zhao, Gang Gao, and Ziyu Guan. "Lesion Segmentation Framework Based on Convolutional Neural Networks with Dual Attention Mechanism." Electronics 10, no. 24 (December 13, 2021): 3103. http://dx.doi.org/10.3390/electronics10243103.
Full textWang, Yaodong, Lili Yue, and Maoqing Li. "Cascaded Searching Reinforcement Learning Agent for Proposal-Free Weakly-Supervised Phrase Comprehension." Electronics 13, no. 5 (February 27, 2024): 898. http://dx.doi.org/10.3390/electronics13050898.
Full textOuassit, Youssef, Reda Moulouki, Mohammed Yassine El Ghoumari, Mohamed Azzouazi, and Soufiane Ardchir. "Liver Segmentation: A Weakly End-to-End Supervised Model." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 09 (August 13, 2020): 77. http://dx.doi.org/10.3991/ijoe.v16i09.15159.
Full textYan, Qing, Tao Sun, Jingjing Zhang, and Lina Xun. "Visibility Estimation Based on Weakly Supervised Learning under Discrete Label Distribution." Sensors 23, no. 23 (November 24, 2023): 9390. http://dx.doi.org/10.3390/s23239390.
Full textZhao, Lulu, Yanan Zhao, Ting Liu, and Hanbing Deng. "A Weakly Supervised Semantic Segmentation Model of Maize Seedlings and Weed Images Based on Scrawl Labels." Sensors 23, no. 24 (December 15, 2023): 9846. http://dx.doi.org/10.3390/s23249846.
Full textZhang, Shuyuan, Hongli Xu, Xiaoran Zhu, and Lipeng Xie. "Automatic Crack Detection Using Weakly Supervised Semantic Segmentation Network and Mixed-Label Training Strategy." Foundations of Computing and Decision Sciences 49, no. 1 (February 1, 2024): 95–118. http://dx.doi.org/10.2478/fcds-2024-0007.
Full textChen, Hao, Shuang Peng, Chun Du, Jun Li, and Songbing Wu. "SW-GAN: Road Extraction from Remote Sensing Imagery Using Semi-Weakly Supervised Adversarial Learning." Remote Sensing 14, no. 17 (August 23, 2022): 4145. http://dx.doi.org/10.3390/rs14174145.
Full textZheng, Shida, Chenshu Chen, Xi Yang, and Wenming Tan. "MaskBooster: End-to-End Self-Training for Sparsely Supervised Instance Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 3 (June 26, 2023): 3696–704. http://dx.doi.org/10.1609/aaai.v37i3.25481.
Full textQiang, Zhuang, Jingmin Shi, and Fanhuai Shi. "Phenotype Tracking of Leafy Greens Based on Weakly Supervised Instance Segmentation and Data Association." Agronomy 12, no. 7 (June 29, 2022): 1567. http://dx.doi.org/10.3390/agronomy12071567.
Full textLiu, Yiqing, Qiming He, Hufei Duan, Huijuan Shi, Anjia Han, and Yonghong He. "Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images." Sensors 22, no. 16 (August 13, 2022): 6053. http://dx.doi.org/10.3390/s22166053.
Full textMo, Shaoyi, Yufeng Shi, Qi Yuan, and Mingyue Li. "A Survey of Deep Learning Road Extraction Algorithms Using High-Resolution Remote Sensing Images." Sensors 24, no. 5 (March 6, 2024): 1708. http://dx.doi.org/10.3390/s24051708.
Full textFan, Yifei. "Image semantic segmentation using deep learning technique." Applied and Computational Engineering 4, no. 1 (June 14, 2023): 810–17. http://dx.doi.org/10.54254/2755-2721/4/2023439.
Full textKuutti, Sampo, Richard Bowden, and Saber Fallah. "Weakly Supervised Reinforcement Learning for Autonomous Highway Driving via Virtual Safety Cages." Sensors 21, no. 6 (March 13, 2021): 2032. http://dx.doi.org/10.3390/s21062032.
Full textWang, Zhuhui, Shijie Wang, Haojie Li, Zhi Dou, and Jianjun Li. "Graph-Propagation Based Correlation Learning for Weakly Supervised Fine-Grained Image Classification." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 12289–96. http://dx.doi.org/10.1609/aaai.v34i07.6912.
Full textCheng, Jianpeng, Siva Reddy, Vijay Saraswat, and Mirella Lapata. "Learning an Executable Neural Semantic Parser." Computational Linguistics 45, no. 1 (March 2019): 59–94. http://dx.doi.org/10.1162/coli_a_00342.
Full textSali, Rasoul, Nazanin Moradinasab, Shan Guleria, Lubaina Ehsan, Philip Fernandes, Tilak U. Shah, Sana Syed, and Donald E. Brown. "Deep Learning for Whole-Slide Tissue Histopathology Classification: A Comparative Study in the Identification of Dysplastic and Non-Dysplastic Barrett’s Esophagus." Journal of Personalized Medicine 10, no. 4 (September 23, 2020): 141. http://dx.doi.org/10.3390/jpm10040141.
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.
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