Literatura académica sobre el tema "Domain adaptation, domain-shift, image classification, neural networks"
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Artículos de revistas sobre el tema "Domain adaptation, domain-shift, image classification, neural networks"
Wang, Xiaoqing y Xiangjun Wang. "Unsupervised Domain Adaptation with Coupled Generative Adversarial Autoencoders". Applied Sciences 8, n.º 12 (7 de diciembre de 2018): 2529. http://dx.doi.org/10.3390/app8122529.
Texto completoS. Garea, Alberto S., Dora B. Heras y Francisco Argüello. "TCANet for Domain Adaptation of Hyperspectral Images". Remote Sensing 11, n.º 19 (30 de septiembre de 2019): 2289. http://dx.doi.org/10.3390/rs11192289.
Texto completoZhao, Fangwen, Weifeng Liu y Chenglin Wen. "A New Method of Image Classification Based on Domain Adaptation". Sensors 22, n.º 4 (9 de febrero de 2022): 1315. http://dx.doi.org/10.3390/s22041315.
Texto completoWang, Jing, Yi He, Wangyi Fang, Yiwei Chen, Wanyue Li y Guohua Shi. "Unsupervised domain adaptation model for lesion detection in retinal OCT images". Physics in Medicine & Biology 66, n.º 21 (22 de octubre de 2021): 215006. http://dx.doi.org/10.1088/1361-6560/ac2dd1.
Texto completoZhao, Sicheng, Chuang Lin, Pengfei Xu, Sendong Zhao, Yuchen Guo, Ravi Krishna, Guiguang Ding y Kurt Keutzer. "CycleEmotionGAN: Emotional Semantic Consistency Preserved CycleGAN for Adapting Image Emotions". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 2620–27. http://dx.doi.org/10.1609/aaai.v33i01.33012620.
Texto completoZhu, Yi, Xinke Zhou y Xindong Wu. "Unsupervised Domain Adaptation via Stacked Convolutional Autoencoder". Applied Sciences 13, n.º 1 (29 de diciembre de 2022): 481. http://dx.doi.org/10.3390/app13010481.
Texto completoRezvaya, Ekaterina, Pavel Goncharov y Gennady Ososkov. "Using deep domain adaptation for image-based plant disease detection". System Analysis in Science and Education, n.º 2 (2020) (30 de junio de 2020): 59–69. http://dx.doi.org/10.37005/2071-9612-2020-2-59-69.
Texto completoMagotra, Arjun y Juntae Kim. "Neuromodulated Dopamine Plastic Networks for Heterogeneous Transfer Learning with Hebbian Principle". Symmetry 13, n.º 8 (26 de julio de 2021): 1344. http://dx.doi.org/10.3390/sym13081344.
Texto completoChengqi Zhang*, Ling Guan** y Zheru Chi. "Introduction to the Special Issue on Learning in Intelligent Algorithms and Systems Design". Journal of Advanced Computational Intelligence and Intelligent Informatics 3, n.º 6 (20 de diciembre de 1999): 439–40. http://dx.doi.org/10.20965/jaciii.1999.p0439.
Texto completoWittich, D. y F. Rottensteiner. "ADVERSARIAL DOMAIN ADAPTATION FOR THE CLASSIFICATION OF AERIAL IMAGES AND HEIGHT DATA USING CONVOLUTIONAL NEURAL NETWORKS". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W7 (16 de septiembre de 2019): 197–204. http://dx.doi.org/10.5194/isprs-annals-iv-2-w7-197-2019.
Texto completoTesis sobre el tema "Domain adaptation, domain-shift, image classification, neural networks"
MAGGIOLO, LUCA. "Deep Learning and Advanced Statistical Methods for Domain Adaptation and Classification of Remote Sensing Images". Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1070050.
Texto completoAhn, Euijoon. "Unsupervised Deep Feature Learning for Medical Image Analysis". Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23002.
Texto completoCapítulos de libros sobre el tema "Domain adaptation, domain-shift, image classification, neural networks"
Ramarolahy, Rija Tonny Christian, Esther Opoku Gyasi y Alessandro Crimi. "Classification and Generation of Microscopy Images with Plasmodium Falciparum via Artificial Neural Networks Using Low Cost Settings". En Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health, 147–57. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87722-4_14.
Texto completoGarrido-Munoz, Carlos, Adrián Sánchez-Hernández, Francisco J. Castellanos y Jorge Calvo-Zaragoza. "Domain Adaptation for Document Image Binarization via Domain Classification". En Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210289.
Texto completoActas de conferencias sobre el tema "Domain adaptation, domain-shift, image classification, neural networks"
Liu, Yujie, Xing Wei, Yang Lu, Chong Zhao y Xuanyuan Qiao. "Source Free Domain Adaptation via Combined Discriminative GAN Model for Image Classification". En 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9891979.
Texto completoLi, Zhide, Ken Cheng, Peiwu Qin, Yuhan Dong, Chengming Yang y Xuefeng Jiang. "Retinal OCT Image Classification Based on Domain Adaptation Convolutional Neural Networks". En 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2021. http://dx.doi.org/10.1109/cisp-bmei53629.2021.9624429.
Texto completoPostadjian, T., A. Le Bris, H. Sahbi y C. Malle. "Domain Adaptation for Large Scale Classification of Very High Resolution Satellite Images with Deep Convolutional Neural Networks". En IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518799.
Texto completoHu, Tao, Shiliang Sun, Jing Zhao y Dongyu Shi. "Enhancing Unsupervised Domain Adaptation via Semantic Similarity Constraint for Medical Image Segmentation". En Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/426.
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