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Hyperspectral imaging (HSI) unlocks the huge potential to a wide variety of applications relied on high-precision pathology image segmentation, such as computational pathology and precision medicine.
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Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, L., Shazeer, N., Ku, A., Tran, D.: Image transformer. In: ICML (2018)
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Sandler, M., Howard, A.G., Zhu, M., Zhmoginov, A., Chen, L.: Mobilenetv2: Inverted residuals and linear bottlenecks. In: CVPR (2018)
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2018
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Correia, G.M., Niculae, V., Martins, A.F.T.: Adaptively sparse transformers. In: Inui, K., Jiang, J., Ng, V., Wan, X. (eds.) EMNLP-IJCNLP (2019)
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Paoletti, M., Haut, J., Plaza, J., Plaza, A.: Deep learning classifiers for hyperspectral imaging: A review. ISPRS Journal of Photogrammetry and Remote Sensing 158
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Zhang, Q., Li, Q., Yu, G., Sun, L., Zhou, M., Chu, J.: A multidimensional choledoch database and benchmarks for cholangiocarcinoma diagnosis. IEEE Access 7
Trajanovski, S., Shan, C., Weijtmans, P.J.C., Brouwer de Koning, S.G., Ruers, T.J.M.: Tongue tumor detection in hyperspectral images using deep learning semantic segmentation. IEEE Trans. Biomedical Engineering (2020)
2020
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2020
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2021
Closest in time.
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., Houlsby, N.: An image is worth 16x16 words: Transformers for image recognition at scale. In: ICLR (2021)
2021
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2019
Cited alongside, same era.
Ortega, S., Halicek, M.T., Fabelo, H., Guerra, R., López, C., Lejeune, M., Godtliebsen, F., Callicó, G.M., Fei, B.: Hyperspectral imaging and deep learning for the detection of breast cancer cells in digitized histological images. In: Medical Imaging: Digital Pathology. SPIE Proceedings, vol. 11320, p. 113200V (2020)
2020
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Closest in time.
2021
Closest in time.
Wang, Q., Sun, L., Wang, Y., Zhou, M., Hu, M., Chen, J., Wen, Y., Li, Q.: Identification of melanoma from hyperspectral pathology image using 3d convolutional networks. IEEE Trans. Medical Imaging 40
2021
Closest in time.