Academic literature on the topic 'Domain adaptation, domain-shift, image classification, neural networks'
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Journal articles on the topic "Domain adaptation, domain-shift, image classification, neural networks"
Wang, Xiaoqing, and Xiangjun Wang. "Unsupervised Domain Adaptation with Coupled Generative Adversarial Autoencoders." Applied Sciences 8, no. 12 (December 7, 2018): 2529. http://dx.doi.org/10.3390/app8122529.
Full textS. Garea, Alberto S., Dora B. Heras, and Francisco Argüello. "TCANet for Domain Adaptation of Hyperspectral Images." Remote Sensing 11, no. 19 (September 30, 2019): 2289. http://dx.doi.org/10.3390/rs11192289.
Full textZhao, Fangwen, Weifeng Liu, and Chenglin Wen. "A New Method of Image Classification Based on Domain Adaptation." Sensors 22, no. 4 (February 9, 2022): 1315. http://dx.doi.org/10.3390/s22041315.
Full textWang, Jing, Yi He, Wangyi Fang, Yiwei Chen, Wanyue Li, and Guohua Shi. "Unsupervised domain adaptation model for lesion detection in retinal OCT images." Physics in Medicine & Biology 66, no. 21 (October 22, 2021): 215006. http://dx.doi.org/10.1088/1361-6560/ac2dd1.
Full textZhao, Sicheng, Chuang Lin, Pengfei Xu, Sendong Zhao, Yuchen Guo, Ravi Krishna, Guiguang Ding, and Kurt Keutzer. "CycleEmotionGAN: Emotional Semantic Consistency Preserved CycleGAN for Adapting Image Emotions." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 2620–27. http://dx.doi.org/10.1609/aaai.v33i01.33012620.
Full textZhu, Yi, Xinke Zhou, and Xindong Wu. "Unsupervised Domain Adaptation via Stacked Convolutional Autoencoder." Applied Sciences 13, no. 1 (December 29, 2022): 481. http://dx.doi.org/10.3390/app13010481.
Full textRezvaya, Ekaterina, Pavel Goncharov, and Gennady Ososkov. "Using deep domain adaptation for image-based plant disease detection." System Analysis in Science and Education, no. 2 (2020) (June 30, 2020): 59–69. http://dx.doi.org/10.37005/2071-9612-2020-2-59-69.
Full textMagotra, Arjun, and Juntae Kim. "Neuromodulated Dopamine Plastic Networks for Heterogeneous Transfer Learning with Hebbian Principle." Symmetry 13, no. 8 (July 26, 2021): 1344. http://dx.doi.org/10.3390/sym13081344.
Full textChengqi Zhang*, Ling Guan**, and Zheru Chi. "Introduction to the Special Issue on Learning in Intelligent Algorithms and Systems Design." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 6 (December 20, 1999): 439–40. http://dx.doi.org/10.20965/jaciii.1999.p0439.
Full textWittich, D., and 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 (September 16, 2019): 197–204. http://dx.doi.org/10.5194/isprs-annals-iv-2-w7-197-2019.
Full textDissertations / Theses on the topic "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.
Full textAhn, Euijoon. "Unsupervised Deep Feature Learning for Medical Image Analysis." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23002.
Full textBook chapters on the topic "Domain adaptation, domain-shift, image classification, neural networks"
Ramarolahy, Rija Tonny Christian, Esther Opoku Gyasi, and Alessandro Crimi. "Classification and Generation of Microscopy Images with Plasmodium Falciparum via Artificial Neural Networks Using Low Cost Settings." In 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.
Full textGarrido-Munoz, Carlos, Adrián Sánchez-Hernández, Francisco J. Castellanos, and Jorge Calvo-Zaragoza. "Domain Adaptation for Document Image Binarization via Domain Classification." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210289.
Full textConference papers on the topic "Domain adaptation, domain-shift, image classification, neural networks"
Liu, Yujie, Xing Wei, Yang Lu, Chong Zhao, and Xuanyuan Qiao. "Source Free Domain Adaptation via Combined Discriminative GAN Model for Image Classification." In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9891979.
Full textLi, Zhide, Ken Cheng, Peiwu Qin, Yuhan Dong, Chengming Yang, and Xuefeng Jiang. "Retinal OCT Image Classification Based on Domain Adaptation Convolutional Neural Networks." In 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.
Full textPostadjian, T., A. Le Bris, H. Sahbi, and C. Malle. "Domain Adaptation for Large Scale Classification of Very High Resolution Satellite Images with Deep Convolutional Neural Networks." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518799.
Full textHu, Tao, Shiliang Sun, Jing Zhao, and Dongyu Shi. "Enhancing Unsupervised Domain Adaptation via Semantic Similarity Constraint for Medical Image Segmentation." In 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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