1. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Denoising in the Deep Learning Era. Artificial Intelligence Review, 000(000):1-46, 2022. Keyword(s): Enhancement/Restoration/Denoising, Machine Learning, Deep Learning, Survey/Review. [bibtex-key = aire2022]



2. Darren Sutton, Zamir K. Punja, and Ghassan Hamarneh. Characterization of Trichome Phenotypes to Assess Maturation and Flower Development in Cannabis sativa L. (Cannabis) by Automatic Trichome Gland Analysis. Smart Agricultural Technology (SAT), 3(100111):1-15, 2022. Keyword(s): Agritech, Precision Agriculture, Plant Phenotyping, Trichomes, Medicinal Cannabis. [bibtex-key = sat2022]

1. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy. In Medical Image Computing and Computer-Assisted Intervention Workshop on Machine Learning for Medical Image Reconstruction (MICCAI MLMIR), volume 11905, pages 236-244, 2019. Keyword(s): Microscopy, Super Resolution, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = miccai_mlmir2019]

1. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Denoising in the Deep Learning Era. Technical report Research Square (Preprint) 1806416, 6 2022. Keyword(s): Deep Learning, Enhancement/Restoration/Denoising, Survey/Review. [bibtex-key = research_square2022_1806416]



2. Darren Sutton, Zamir K. Punja, and Ghassan Hamarneh. Characterization of Trichome Phenotypes to Assess Maturation and Flower Development in Cannabis sativa L. (Cannabis) by Automatic Trichome Gland Analysis. Technical report SSRN Electronic Journal 4141209, 6 2022. Keyword(s): Agritech, Precision Agriculture, Plant Phenotyping, Trichomes, Medicinal Cannabis. [bibtex-key = ssrn2022_4141209]



3. Saeed Izadi, Darren Sutton, and Ghassan Hamarneh. Image Super Resolution via Bilinear Pooling: Application to Confocal Endomicroscopy. Technical report arxiv:1906.07802, 6 2019. Keyword(s): Microscopy, Super Resolution, Enhancement/Restoration/Denoising, Machine Learning, Deep Learning. [bibtex-key = arxiv:1906.07802]

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