SRZoo: An integrated repository for super-resolution using deep learning

Deep learning-based image processing algorithms, including image super-resolution methods, have been proposed with significant improvement in performance in recent years. However, their implementations and evaluations are dispersed in terms of various deep learning frameworks and various evaluation criteria. In this paper, we propose an integrated repository for the super-resolution tasks, named SRZoo, to provide state-of-the-art super-resolution models in a single place. Our repository offers not only converted versions of existing pre-trained models, but also documentation and toolkits for converting other models. In addition, SRZoo provides platform-agnostic image reconstruction tools to obtain super-resolved images and evaluate the performance in place. It also brings the opportunity of extension to advanced image-based researches and other image processing models. The software, documentation, and pre-trained models are publicly available on GitHub.Comment: Accepted in ICASSP 2020, code available at https://github.com/idearibosome/srzo

???????????? ??? ?????? ?????? ????????? ????????? ??????????????? ????????? ????????? ????????? ?????????

Department of ChemistryRecently, irradiation of visible light photoredox catalyst has been widely used to drive transformation of organic molecules though the highly desirable processes. Absorption of visible light induces the long-lived excited-triplet state of the photocatalyst. The returning from this excited state to the bench state of the catalyst leads single-electron-transfer (SET), transforming the reacting substrates into radical intermediates. The radical cation/anion intermediates show their reactivity which is basically differentiated from those of electronically ground state of molecules. Multicomponent reaction (MCR) serves as a powerful tool, employing three or more simple building blocks to produce complex molecular frameworks in a single step. Given its advantages of rapid access to structural complexity, MCR has been adopted as a valuable means for the discovery of bioactive compounds. As such, photoredox catalysis has been explored in the context of MCR. However, the limited examples are mostly based on radical-polar crossover mechanisms, in which the process is in operation for initial coupling of two reactants, while a third component is incorporated via a polar process. Although this approach is useful, quenching of radical processes by redox catalysts entailing the involvement of polar processes poses limitations in the scope of coupling partners. To the best of our knowledge, MCR with three consecutive bond formation based on radical processes via visible-light photoredox catalysis has not been reported. Due to their utilities, significant efforts have been made to develop efficient synthetic methods for quinolines. However, the conventional methods rely on condensation under harsh conditions and more recent developments are limited to transitional metal-catalyzed and iodine-mediated synthesis. Here, a successful development of a new tandem radical cyclization based on visible-light photoredox catalysis enables the efficient formation of quinolines based on consecutive radical processes.ope