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Detection of retinal microlesions through YOLOR-CSP architecture and image slicing with the SAHI algorithm.

, , , , , , and . IJCNN, page 1-8. IEEE, (2023)

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azaad@BND at SemEval-2023 Task 2: How to Go from a Simple Transformer Model to a Better Model to Get Better Results in Natural Language Processing., , and . SemEval@ACL, page 2184-2187. Association for Computational Linguistics, (2023)mCUTE: A Model-Level Concolic Unit Testing Engine for UML State Machines., , and . ASE, page 1182-1185. IEEE, (2019)Leveraging modeling concepts and techniques to address challenges in network management., , , and . MODELS, page 55-61. IEEE, (2023)Experimental Realization of a Reconfigurable Three Input, One Output Logic Function Based on a Chaotic Circuit., , , and . Int. J. Bifurc. Chaos, 20 (3): 715-726 (2010)Partial triangular entropy of uncertain random variables and its application., , , and . J. Ambient Intell. Humaniz. Comput., 9 (5): 1455-1464 (2018)Slicing UML-based Models of Real-time Embedded Systems., , and . MoDELS, page 346-356. ACM, (2018)Cooperative load sharing in V2G application., , and . EIT, page 451-456. IEEE, (2015)Concolic testing for models of state-based systems., and . ESEC/SIGSOFT FSE, page 4-15. ACM, (2019)Detection of retinal microlesions through YOLOR-CSP architecture and image slicing with the SAHI algorithm., , , , , , and . IJCNN, page 1-8. IEEE, (2023)A Multi-Agent Deep Reinforcement Learning Approach for a Distributed Energy Marketplace in Smart Grids., , , , , and . SmartGridComm, page 1-6. IEEE, (2020)