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Two-Stage Transfer Learning for Fusion and Classification of Airborne Hyperspectral Imagery
In this work, we introduce a novel fusion and training strategy aimed at facilitating transfer
learning to enhance classification in hyperspectral airborne imagery. Our training strategy …
learning to enhance classification in hyperspectral airborne imagery. Our training strategy …
S4DL: Shift-sensitive Spatial-Spectral Disentangling Learning for Hyperspectral Image Unsupervised Domain Adaptation
Unsupervised domain adaptation techniques, extensively studied in hyperspectral image
(HSI) classification, aim to use labeled source domain data and unlabeled target domain …
(HSI) classification, aim to use labeled source domain data and unlabeled target domain …
Cross-Domain Text Classification: Transfer Learning Approaches
HJ Asha, JA Josephine - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
Natural language processing faces a difficulty with cross-domain text classification (CDTC),
as models trained on one domain's data frequently find it difficult to generalize well to other …
as models trained on one domain's data frequently find it difficult to generalize well to other …
[PDF][PDF] Cross-Domain Text Classification: Transfer Learning Approaches
MP Scholar - erp.holycrossngl.edu.in
Natural language processing faces a difficulty with cross-domain text classification (CDTC),
as models trained on one domain's data frequently find it difficult to generalize well to other …
as models trained on one domain's data frequently find it difficult to generalize well to other …