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OA期刊


ISSN1573-7462
刊名The Artificial intelligence review
出版商Springer
urlhttps://link.springer.com/journal/10462



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2023, vol.56, no.1 2023, vol.56, no.10 2023, vol.56, no.11 2023, vol.56, no.12 2023, vol.56, no.2 2023, vol.56, no.3
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2023, vol.56, no.S1 2023, vol.56, no.S2 2023, vol.56, no.S3

题名作者出版年年卷期
Machine learning for leaf disease classification: data, techniques and applicationsJianping Yao;Son N. Tran;Samantha Sawyer;Saurabh Garg;20232023, vol.56, no.S3
Deep neural network techniques for monaural speech enhancement and separation: state of the art analysisPeter Ochieng;20232023, vol.56, no.S3
Mobility trajectory generation: a surveyXiangjie Kong;Qiao Chen;Mingliang Hou;Hui Wang;Feng Xia;20232023, vol.56, no.S3
Machine and deep learning for longitudinal biomedical data: a review of methods and applicationsAnna Cascarano;Jordi Mur-Petit;Jerónimo Hernández-González;Marina Camacho;Nina de Toro Eadie;Polyxeni Gkontra;Marc Chadeau-Hyam;Jordi Vitrià;Karim Lekadir;20232023, vol.56, no.S2
A systematic review of federated learning from clients’ perspective: challenges and solutionsYashothara Shanmugarasa;Hye-young Paik;Salil S. Kanhere;Liming Zhu;20232023, vol.56, no.S2
Soft computing techniques for biomedical data analysis: open issues and challengesEssam H. Houssein;Mosa E. Hosney;Marwa M. Emam;Eman M. G. Younis;Abdelmgeid A. Ali;Waleed M. Mohamed;20232023, vol.56, no.S2
Artificial glial cells in artificial neuronal networks: a systematic reviewSara Alvarez-Gonzalez;Francisco Cedron;Alejandro Pazos;Ana B. Porto-Pazos;20232023, vol.56, no.S2
A practical utility-based but objective approach to model selection for regression in scientific applicationsAndrea Murari;Riccardo Rossi;Luca Spolladore;Michele Lungaroni;Pasquale Gaudio;Michela Gelfusa;20232023, vol.56, no.S2
A systematic review of deep learning-based cervical cytology screening: from cell identification to whole slide image analysisPeng Jiang;Xuekong Li;Hui Shen;Yuqi Chen;Lang Wang;Hua Chen;Jing Feng;Juan Liu;20232023, vol.56, no.S2
Safety-critical computer vision: an empirical survey of adversarial evasion attacks and defenses on computer vision systemsCharles Meyers;Tommy Löfstedt;Erik Elmroth;20232023, vol.56, no.S1
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