Artykuły w czasopismach na temat „Shortcut learning”
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Kim, Doyoung, Dongmin Park, Yooju Shin, Jihwan Bang, Hwanjun Song i Jae-Gil Lee. "Adaptive Shortcut Debiasing for Online Continual Learning". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 12 (24.03.2024): 13122–31. http://dx.doi.org/10.1609/aaai.v38i12.29211.
Pełny tekst źródłaNauta, Meike, Ricky Walsh, Adam Dubowski i Christin Seifert. "Uncovering and Correcting Shortcut Learning in Machine Learning Models for Skin Cancer Diagnosis". Diagnostics 12, nr 1 (24.12.2021): 40. http://dx.doi.org/10.3390/diagnostics12010040.
Pełny tekst źródłaGeirhos, Robert, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge i Felix A. Wichmann. "Shortcut learning in deep neural networks". Nature Machine Intelligence 2, nr 11 (listopad 2020): 665–73. http://dx.doi.org/10.1038/s42256-020-00257-z.
Pełny tekst źródłaFay, Louisa, Erick Cobos, Bin Yang, Sergios Gatidis i Thomas Küstner. "Avoiding Shortcut-Learning by Mutual Information Minimization in Deep Learning-Based Image Processing". IEEE Access 11 (2023): 64070–86. http://dx.doi.org/10.1109/access.2023.3289397.
Pełny tekst źródłaPOTAPOV, ALEXEI B., i M. K. ALI. "LEARNING, EXPLORATION AND CHAOTIC POLICIES". International Journal of Modern Physics C 11, nr 07 (październik 2000): 1455–64. http://dx.doi.org/10.1142/s0129183100001309.
Pełny tekst źródłaMORIHIRO, KOICHIRO, NOBUYUKI MATSUI i HARUHIKO NISHIMURA. "CHAOTIC EXPLORATION EFFECTS ON REINFORCEMENT LEARNING IN SHORTCUT MAZE TASK". International Journal of Bifurcation and Chaos 16, nr 10 (październik 2006): 3015–22. http://dx.doi.org/10.1142/s0218127406016616.
Pełny tekst źródłaDu, Mengnan, Fengxiang He, Na Zou, Dacheng Tao i Xia Hu. "Shortcut Learning of Large Language Models in Natural Language Understanding". Communications of the ACM 67, nr 1 (21.12.2023): 110–20. http://dx.doi.org/10.1145/3596490.
Pełny tekst źródłaHAN, FANG, MARIAN WIERCIGROCH, JIAN-AN FANG i ZHIJIE WANG. "EXCITEMENT AND SYNCHRONIZATION OF SMALL-WORLD NEURONAL NETWORKS WITH SHORT-TERM SYNAPTIC PLASTICITY". International Journal of Neural Systems 21, nr 05 (październik 2011): 415–25. http://dx.doi.org/10.1142/s0129065711002924.
Pełny tekst źródłaHu, Ruilin, Yajun Du, Jingrong Hu i Hui Li. "Cross-community shortcut detection based on network representation learning and structural features". Intelligent Data Analysis 27, nr 3 (18.05.2023): 709–32. http://dx.doi.org/10.3233/ida-216513.
Pełny tekst źródłaZhong, Yujie, Xiao Li, Jiangjian Xie i Junguo Zhang. "A Lightweight Automatic Wildlife Recognition Model Design Method Mitigating Shortcut Learning". Animals 13, nr 5 (25.02.2023): 838. http://dx.doi.org/10.3390/ani13050838.
Pełny tekst źródłaTrivedi, Anusua, Caleb Robinson, Marian Blazes, Anthony Ortiz, Jocelyn Desbiens, Sunil Gupta, Rahul Dodhia i in. "Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement". PLOS ONE 17, nr 10 (6.10.2022): e0274098. http://dx.doi.org/10.1371/journal.pone.0274098.
Pełny tekst źródłaLao, Mingrui, Nan Pu, Yu Liu, Kai He, Erwin M. Bakker i Michael S. Lew. "COCA: COllaborative CAusal Regularization for Audio-Visual Question Answering". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 11 (26.06.2023): 12995–3003. http://dx.doi.org/10.1609/aaai.v37i11.26527.
Pełny tekst źródłaNatsir, Siti Zahra Mulianti, Bibin Rubini, Didit Ardianto i Nurhaedah Madjid. "Interactive Learning Multimedia: A Shortcut for Boosting Gen-Z’s Digital literacy in Science Classroom". Jurnal Penelitian Pendidikan IPA 8, nr 5 (30.11.2022): 2168–75. http://dx.doi.org/10.29303/jppipa.v8i5.1897.
Pełny tekst źródłaFathima, Sheeba. "Music Genre Classification using Deep Learning". International Journal for Research in Applied Science and Engineering Technology 9, nr VII (10.07.2021): 66–71. http://dx.doi.org/10.22214/ijraset.2021.36087.
Pełny tekst źródłaRees, Simon, Megan Bruce i Steven Bradley. "Utilising data-driven learning in chemistry teaching: A shortcut to improving chemical language comprehension". New Directions in the Teaching of Physical Sciences, nr 10 (1.06.2014): 12–19. http://dx.doi.org/10.29311/ndtps.v0i10.511.
Pełny tekst źródłaRees, Simon, Megan Bruce i Steven Bradley. "Utilising Data-driven Learning in Chemistry Teaching: a Shortcut to Improving Chemical Language Comprehension". New Directions 10, nr 1 (czerwiec 2014): 12–19. http://dx.doi.org/10.11120/ndir.2014.00028.
Pełny tekst źródłaWilkinson, Anna, Karin Kuenstner, Julia Mueller i Ludwig Huber. "Social learning in a non-social reptile ( Geochelone carbonaria )". Biology Letters 6, nr 5 (31.03.2010): 614–16. http://dx.doi.org/10.1098/rsbl.2010.0092.
Pełny tekst źródłaMengue-Topio, Hursula, Yannick Courbois, Emily K. Farran i Pascal Sockeel. "Route learning and shortcut performance in adults with intellectual disability: A study with virtual environments". Research in Developmental Disabilities 32, nr 1 (styczeń 2011): 345–52. http://dx.doi.org/10.1016/j.ridd.2010.10.014.
Pełny tekst źródłaClegg, Benjamin A. "Stimulus-Specific Sequence Representation in Serial Reaction Time Tasks". Quarterly Journal of Experimental Psychology Section A 58, nr 6 (sierpień 2005): 1087–101. http://dx.doi.org/10.1080/02724980443000485.
Pełny tekst źródłaSong, Rui, Fausto Giunchiglia, Yingji Li, Mingjie Tian i Hao Xu. "TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 17 (24.03.2024): 18999–9007. http://dx.doi.org/10.1609/aaai.v38i17.29866.
Pełny tekst źródłaSuparjan, Suparjan, i Nining Ismiyani. "The Use of Tanjungpura University’s e-Learning-Moodle LMS during Online Learning: Problems, Solutions and Continuation". Ta'dib 26, nr 1 (25.06.2023): 71. http://dx.doi.org/10.31958/jt.v26i1.7902.
Pełny tekst źródłaHusain, Arshi, i Virendra P. Vishvakarma. "Optimized deterministic multikernel extreme learning machine for classification of COVID-19 chest Xray images". Journal of Information and Optimization Sciences 44, nr 4 (2023): 771–93. http://dx.doi.org/10.47974/jios-1319.
Pełny tekst źródłaXu, Chendong, Weigang Wang, Yunwei Zhang, Jie Qin, Shujuan Yu i Yun Zhang. "An Indoor Localization System Using Residual Learning with Channel State Information". Entropy 23, nr 5 (7.05.2021): 574. http://dx.doi.org/10.3390/e23050574.
Pełny tekst źródłaArun, K., i A. Srinagesh. "Multilingual twitter sentiment analysis using machine learning". International Journal of Electrical and Computer Engineering (IJECE) 10, nr 6 (1.12.2020): 5992. http://dx.doi.org/10.11591/ijece.v10i6.pp5992-6000.
Pełny tekst źródłaZheng, Hui, Yizhi Cao, Min Sun, Guihai Guo, Junzhen Meng, Xinwei Guo i Yanchi Jiang. "Mixed Structure with 3D Multi-Shortcut-Link Networks for Hyperspectral Image Classification". Remote Sensing 14, nr 5 (2.03.2022): 1230. http://dx.doi.org/10.3390/rs14051230.
Pełny tekst źródłaHolmberg, Linn. "Right and Wrong Ways of Knowing". 1700-tal: Nordic Journal for Eighteenth-Century Studies 20 (20.12.2023): 8–33. http://dx.doi.org/10.7557/4.7203.
Pełny tekst źródłaSun, Chaoyue, Ruogu Fang, Marco Salemi, Mattia Prosperi i Brittany Rife Magalis. "DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction". PLOS Computational Biology 20, nr 4 (10.04.2024): e1011351. http://dx.doi.org/10.1371/journal.pcbi.1011351.
Pełny tekst źródłaThanuja, B. "Machine Learning Based Crime Rate Analysis Using Python". International Journal for Research in Applied Science and Engineering Technology 10, nr 11 (30.11.2022): 1312–16. http://dx.doi.org/10.22214/ijraset.2022.47574.
Pełny tekst źródłaWelte, Peter O. "Caveat Examiner: Beware Clever Students". Perceptual and Motor Skills 77, nr 3_suppl (grudzień 1993): 1213–14. http://dx.doi.org/10.2466/pms.1993.77.3f.1213.
Pełny tekst źródłaPollock, Mica. "Flipping Our Scripts about Undocumented Immigration". Genealogy 4, nr 1 (19.03.2020): 29. http://dx.doi.org/10.3390/genealogy4010029.
Pełny tekst źródłaPetrov, Sergei, Tapan Mukerji, Xin Zhang i Xinfei Yan. "Shape Carving Methods of Geologic Body Interpretation from Seismic Data Based on Deep Learning". Energies 15, nr 3 (31.01.2022): 1064. http://dx.doi.org/10.3390/en15031064.
Pełny tekst źródłaMah, Christopher, Hillary Walker, Lena Phalen, Sarah Levine, Sarah W. Beck i Jaylen Pittman. "Beyond CheatBots: Examining Tensions in Teachers’ and Students’ Perceptions of Cheating and Learning with ChatGPT". Education Sciences 14, nr 5 (7.05.2024): 500. http://dx.doi.org/10.3390/educsci14050500.
Pełny tekst źródłaWang, Tong, Yuan Yao, Feng Xu, Miao Xu, Shengwei An i Ting Wang. "Inspecting Prediction Confidence for Detecting Black-Box Backdoor Attacks". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 1 (24.03.2024): 274–82. http://dx.doi.org/10.1609/aaai.v38i1.27780.
Pełny tekst źródłaSulistyo, Totok, i Rohmat Fauzi. "Soil Infiltration Rate Prediction using Machine Learning Regression Model: A Case Study on Sepinggan River Basin, Balikpapan, Indonesia". Indonesian Journal on Geoscience 10, nr 3 (23.11.2023): 335–47. http://dx.doi.org/10.17014/ijog.10.3.335-347.
Pełny tekst źródłaRamsgaard Thomsen, Mette, Paul Nicholas, Martin Tamke, Sebastian Gatz, Yuliya Sinke i Gabriella Rossi. "Towards machine learning for architectural fabrication in the age of industry 4.0". International Journal of Architectural Computing 18, nr 4 (17.08.2020): 335–52. http://dx.doi.org/10.1177/1478077120948000.
Pełny tekst źródłaKURAKAMI, Takeru, Kazuyoshi SOUMA, Takashi MIYAMOTO, Takahiko FURUYA, Jun MAGOME i Hiroshi ISHIDAIRA. "APPLICATION OF A DEEP-LEARNING METHOD INCLUDING SHORTCUT PATHS TO CORRECT THE PRECIPITATION OUTPUTS OF A NUMERICAL WEATHER PREDICTION MODEL". Journal of Japan Society of Civil Engineers, Ser. G (Environmental Research) 76, nr 5 (2020): I_471—I_478. http://dx.doi.org/10.2208/jscejer.76.5_i_471.
Pełny tekst źródłaLópez-Cabrera, José Daniel, Rubén Orozco-Morales, Jorge Armando Portal-Díaz, Orlando Lovelle-Enríquez i Marlén Pérez-Díaz. "Current limitations to identify covid-19 using artificial intelligence with chest x-ray imaging (part ii). The shortcut learning problem". Health and Technology 11, nr 6 (10.10.2021): 1331–45. http://dx.doi.org/10.1007/s12553-021-00609-8.
Pełny tekst źródłaZhao, Yu, Rennong Yang, Guillaume Chevalier, Ximeng Xu i Zhenxing Zhang. "Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors". Mathematical Problems in Engineering 2018 (30.12.2018): 1–13. http://dx.doi.org/10.1155/2018/7316954.
Pełny tekst źródłaJ, Kamalakannan, i Chandana Mani R K. "ERNet : Enhanced ResNet for classification of breast histopathological images". ELCVIA Electronic Letters on Computer Vision and Image Analysis 22, nr 2 (14.03.2024): 53–68. http://dx.doi.org/10.5565/rev/elcvia.1614.
Pełny tekst źródłaHe, Z., H. He, J. Li, M. A. Chapman i H. Ding. "A SHORT-CUT CONNECTIONS-BASED NEURAL NETWORK FOR BUILDING EXTRACTION FROM HIGH RESOLUTION ORTHOIMAGERY". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2022 (30.05.2022): 39–44. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2022-39-2022.
Pełny tekst źródłaLiu, Yao, Lianru Gao, Chenchao Xiao, Ying Qu, Ke Zheng i Andrea Marinoni. "Hyperspectral Image Classification Based on a Shuffled Group Convolutional Neural Network with Transfer Learning". Remote Sensing 12, nr 11 (1.06.2020): 1780. http://dx.doi.org/10.3390/rs12111780.
Pełny tekst źródłaXu, Pengcheng, Zhongyuan Guo, Lei Liang i Xiaohang Xu. "MSF-Net: Multi-Scale Feature Learning Network for Classification of Surface Defects of Multifarious Sizes". Sensors 21, nr 15 (29.07.2021): 5125. http://dx.doi.org/10.3390/s21155125.
Pełny tekst źródłaMalik, Sohail Iqbal, Mohanaad Shakir, Abdalla Eldow i Mohammed Waseem Ashfaque. "Promoting Algorithmic Thinking in an Introductory Programming Course". International Journal of Emerging Technologies in Learning (iJET) 14, nr 01 (17.01.2019): 84. http://dx.doi.org/10.3991/ijet.v14i01.9061.
Pełny tekst źródłaDevaney, Kirsty. "‘Waiting for the wow factor’: Perspectives on computer technology in classroom composing". Journal of Music, Technology & Education 12, nr 2 (1.09.2019): 121–39. http://dx.doi.org/10.1386/jmte_00002_1.
Pełny tekst źródłaXu, Yao, i Qin Yu. "Adaptive Weighted Multi-Level Fusion of Multi-Scale Features: A New Approach to Pedestrian Detection". Future Internet 13, nr 2 (2.02.2021): 38. http://dx.doi.org/10.3390/fi13020038.
Pełny tekst źródłaXie, Zhousan, Shikui Tu i Lei Xu. "Multilevel Attention Network with Semi-supervised Domain Adaptation for Drug-Target Prediction". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 1 (24.03.2024): 329–37. http://dx.doi.org/10.1609/aaai.v38i1.27786.
Pełny tekst źródłaMohamed, Islam A., Adel Othman i Mohamed Fathy. "A new approach to improve reservoir modeling via machine learning". Leading Edge 39, nr 3 (marzec 2020): 170–75. http://dx.doi.org/10.1190/tle39030170.1.
Pełny tekst źródłaZakareya, Salman, Habib Izadkhah i Jaber Karimpour. "A New Deep-Learning-Based Model for Breast Cancer Diagnosis from Medical Images". Diagnostics 13, nr 11 (1.06.2023): 1944. http://dx.doi.org/10.3390/diagnostics13111944.
Pełny tekst źródłaHe, Anzheng, Zishuo Dong, Hang Zhang, Allen A. Zhang, Shi Qiu, Yang Liu, Kelvin C. P. Wang i Zhihao Lin. "Automated Pixel-Level Detection of Expansion Joints on Asphalt Pavement Using a Deep-Learning-Based Approach". Structural Control and Health Monitoring 2023 (23.05.2023): 1–15. http://dx.doi.org/10.1155/2023/7552337.
Pełny tekst źródłaZhang, Xuetao, Kuangang Fan, Haonan Hou i Chuankai Liu. "Real-Time Detection of Drones Using Channel and Layer Pruning, Based on the YOLOv3-SPP3 Deep Learning Algorithm". Micromachines 13, nr 12 (11.12.2022): 2199. http://dx.doi.org/10.3390/mi13122199.
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