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A comparison of methods for image classification of cultural heritage using transfer learning for feature extraction
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A comparison of methods for image classification of cultural heritage using transfer learning for feature extraction

Janković Babić, Radmila

Neural computing & applications, 2024-07, Vol.36 (20), p.11699-11709 [Periódico revisado por pares]

London: Springer London

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Semi-supervised multi-source transfer learning for cross-subject EEG motor imagery classification
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Semi-supervised multi-source transfer learning for cross-subject EEG motor imagery classification

Zhang, Fan ; Wu, Hanliang ; Guo, Yuxin

Medical & biological engineering & computing, 2024-06, Vol.62 (6), p.1655-1672 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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A Deep Learning-based System for Detecting Anemia from Eye Conjunctiva Images taken from a Smartphone
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A Deep Learning-based System for Detecting Anemia from Eye Conjunctiva Images taken from a Smartphone

Pallavi ; Basumatary, Bijit ; Shukla, Rahul ; Kumar, Rakesh ; Das, Bodhisatwa ; Sahani, Ashish Kumar

Technical review - IETE, 2024-05, Vol.41 (3), p.274-286 [Periódico revisado por pares]

Taylor & Francis

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4
CNN-based hot-rolled steel strip surface defects classification: a comparative study between different pre-trained CNN models
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CNN-based hot-rolled steel strip surface defects classification: a comparative study between different pre-trained CNN models

Bouguettaya, Abdelmalek ; Zarzour, Hafed

International journal of advanced manufacturing technology, 2024-05, Vol.132 (1-2), p.399-419 [Periódico revisado por pares]

London: Springer London

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5
Enhanced multi-level features for very high resolution remote sensing scene classification
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Enhanced multi-level features for very high resolution remote sensing scene classification

Sitaula, Chiranjibi ; KC, Sumesh ; Aryal, Jagannath

Neural computing & applications, 2024-05, Vol.36 (13), p.7071-7083 [Periódico revisado por pares]

London: Springer London

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6
Multimodal meta-learning through meta-learned task representations
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Multimodal meta-learning through meta-learned task representations

Vettoruzzo, Anna ; Bouguelia, Mohamed-Rafik ; Rögnvaldsson, Thorsteinn

Neural computing & applications, 2024-05, Vol.36 (15), p.8519-8529 [Periódico revisado por pares]

London: Springer London

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7
Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G
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Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G

Lim, Wei Xiang ; Chen, Zhiyuan

Medical & biological engineering & computing, 2024-04 [Periódico revisado por pares]

United States

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8
Adaptive vertical federated learning via feature map transferring in mobile edge computing
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Adaptive vertical federated learning via feature map transferring in mobile edge computing

Li, Yuanzhang ; Sha, Tianchi ; Baker, Thar ; Yu, Xiao ; Shi, Zhiwei ; Hu, Sikang

Computing, 2024-04, Vol.106 (4), p.1081-1097 [Periódico revisado por pares]

Vienna: Springer Vienna

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9
Empowering EEG motor imagery classification with deep transfer learning approach
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Empowering EEG motor imagery classification with deep transfer learning approach

Mishra, Awanish Kumar ; Gupta, Indresh Kumar ; Srivastava, Swati ; Alfarhood, Sultan ; Safran, Mejdl

Expert systems, 2024-04, Vol.41 (4), p.n/a [Periódico revisado por pares]

Oxford: Blackwell Publishing Ltd

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10
Parameter‐based transfer learning for severity classification of atopic dermatitis using hyperspectral imaging
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Parameter‐based transfer learning for severity classification of atopic dermatitis using hyperspectral imaging

Kim, Eun Bin ; Baek, Yoo Sang ; Lee, Onseok

Skin research and technology, 2024-04, Vol.30 (4), p.e13704-n/a [Periódico revisado por pares]

England: John Wiley & Sons, Inc

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