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Academic Journal

How Well Do Vision Transformers (VTs) Transfer to the Non-natural Image Domain? An Empirical Study Involving Art Classification

Subjects: Art classification; Convolutional Neural Networks; Transfer learning

  • Source: Tonkes , V & Sabatelli , M 2023 , How Well Do Vision Transformers (VTs) Transfer to the Non-natural Image Domain? An Empirical Study Involving Art Classification . in L Karlinsky , T Michaeli & K

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Academic Journal

Towards Robust Colour Texture Classification with Limited Training Data

Subjects: adaptive dissimilarity; Colour texture classification; Learning Vector Quantization

  • Source: Shumska , M & Bunte , K 2023 , Towards Robust Colour Texture Classification with Limited Training Data . in N Tsapatsoulis , E Kyriacou , A Lanitis , Z Theodosiou , M Pattichis , C Pattichis , C

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Academic Journal

Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging:A Transfer Learning Approach

Subjects: Auto contouring; Deep learning; Head and neck cancer

  • Source: Chu , H , De la O Arévalo , L R , Tang , W , Ma , B , Li , Y , De Biase , A , Both , S , Langendijk , J A , van Ooijen , P , Sijtsema , N M & van Dijk , L V 2023 , Swin UNETR for Tumor and Lymph Node

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Academic Journal

Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients

Subjects: Deep learning; Head and neck cancer; Oropharyngeal cancer

  • Source: Ma , B , Li , Y , Chu , H , Tang , W , De la O Arévalo , L R , Guo , J , van Ooijen , P , Both , S , Langendijk , J A , van Dijk , L V & Sijtsema , N M 2023 , Deep

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Academic Journal

Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images

Subjects: AI; Automatic segmentation; Co-learning

  • Source: De Biase , A , Tang , W , Sourlos , N , Ma , B , Guo , J , Sijtsema , N M & van Ooijen , P 2022 , Skip-SCSE Multi-scale Attention and Co-learning Method for

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Academic Journal

On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

Subjects: Bayesian games; Distributed optimisation; Fictitious play

  • Source: Smyrnakis , M , Qu , H , Bauso , D & Veres , S 2021 , On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters . in A P Rocha , L Steels & J van

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