2026-04-14T07:58:05Zhttps://recercat.cat/oai/request

oai:recercat.cat:20.500.12327/30352025-10-22T11:07:39Zcom_2072_4428com_2072_4427col_2072_487898

A short note on deep contextual spatial and spectral information fusion for hyperspectral image processing: Case of pork belly properties prediction Mishra, Puneet Albano-Gaglio, Michela Font-i-Furnols, Maria Indústries Alimentàries Qualitat i Tecnologia Alimentària This study demonstrates a new approach to process hyperspectral images where both the contextual spatial information as well as the spectral information are used to predict sample properties. The deep contextual spatial information is extracted using the deep feature extraction from pretrained resnet-18 deep learning architecture, while the spectral information was readily available as the average pixel values. To fuse the information in a complementary way, a multiblock modeling approach called sequential orthogonalized partial least squares was used. The sequential model guarantees that the information learned is complementary from spatial and spectral domains. The potential of the approach is demonstrated to predict several physical and chemical properties in pork bellies. 2025-10-22T11:07:39Z 2025-10-22T11:07:39Z 2025-10-22T11:07:39Z 2024-04-18 info:eu-repo/semantics/article Mishra, Puneet, Michela Albano‐Gaglio, and Maria Font‐i‐Furnols. 2024. “A short note on deep contextual spatial and spectral information fusion for hyperspectral image processing: Case of pork belly properties prediction”. Journal of Chemometrics, April. doi:10.1002/cem.3552. 0886-9383 http://hdl.handle.net/20.500.12327/3035 https://doi.org/10.1002/cem.3552 eng Journal of Chemometrics MICIU/Programa Estatal de I+D+I orientada a los retos de la sociedad/RTI2018-096993-B-I00/ES/CLASIFICACION Y EVALUACION DE LA CALIDAD GLOBAL DE LA PANCETA DE CERDO MEDIANTE TECNOLOGIAS NO DESTRUCTIVAS Y PERCEPCION POR PARTE DE LOS CONSUMIDORES/ http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Attribution 4.0 International Wiley