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EMScan : une application mobile pour l'assistance au diagnostic des formes précoces de la maladie de Lyme., , , , , , and . EGC, volume E-39 of RNTI, page 613-620. Editions RNTI, (2023)Contribution to multimodal classification problem with data scarcity : application to the early diagnosis of Lyme disease. (Contribution à la classification multimodale dans le cas d'une rareté de données : application au diagnostic précoce de la maladie de Lyme).. University of Clermont Auvergne, Clermont-Ferrand, France, (2023)Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images., , , , , , , , , and 13 other author(s). Comput. Methods Programs Biomed., (2022)Benchmarking convolutional neural networks for diagnosing Lyme disease from images., , , , , , , , , and 9 other author(s). CoRR, (2021)Expert Opinion Elicitation for Assisting Deep Learning based Lyme Disease Classifier with Patient Data., , , , , , , , and . CoRR, (2022)Optimization of University Course Scheduling Problem using Particle Swarm Optimization with Selective Search., , , , and . Expert Syst. Appl., (2019)ResVMAC: A Novel Medium Access Control Protocol for Vehicular Ad hoc Networks., , , and . ANT/SEIT, volume 109 of Procedia Computer Science, page 432-439. Elsevier, (2017)Early Diagnosis of Lyme Disease by Recognizing Erythema Migrans Skin Lesion from Images Utilizing Deep Learning Techniques.. IJCAI, page 5855-5856. ijcai.org, (2022)