Citation: Elshahawy, M.; Elnemr, A.; Oproescu, M.; Schiopu, A.-G.; Elgarayhi, A.; Elmogy, M.M.; Sallah, M. Early Melanoma Detection Based on a Hybrid YOLOv5 and ResNet Technique. Diagnostics 2023, 13, 2804. https://doi.org/10.3390/ diagnostics13172804 Academic Editor: Dechang Chen Received: 25 July 2023 Revised: 11 August 2023 Accepted: 22 August 2023 Published: 30 August 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). diagnostics Article Early Melanoma Detection Based on a Hybrid YOLOv5 and ResNet Technique Manar Elshahawy 1,† , Ahmed Elnemr 2,† , Mihai Oproescu 3, * , Adriana-Gabriela Schiopu 4 , Ahmed Elgarayhi 2 , Mohammed M. Elmogy 1, * ,‡ and Mohammed Sallah 5,‡ 1 Information Technology Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt; manarelshahawy@mans.edu.eg 2 Applied Mathematical Physics Research Group, Physics Department, Faculty of Science, Mansoura University, Mansoura 35516, Egypt; ahmedelnemr@mans.edu.eg (A.E.); elgarayhi@mans.edu.eg (A.E.) 3 Faculty of Electronics, Communication, and Computer Science, University of Pitesti, 110040 Pitesti, Romania 4 Department of Manufacturing and Industrial Management, Faculty of Mechanics and Technology, University of Pitesti, 110040 Pitesti, Romania; gabriela.plaiasu@upit.ro 5 Department of Physics, College of Sciences, University of Bisha, P.O. Box 344, Bisha 61922, Saudi Arabia; msallahd@mans.edu.eg * Correspondence: mihai.oproescu@upit.ro (M.O.); melmogy@mans.edu.eg (M.M.E.) † The authors contributed equally to this work and shared the first authorship. ‡ The authors share the senior authorship. Abstract: Skin cancer, specifically melanoma, is a serious health issue that arises from the melanocytes, the cells that produce melanin, the pigment responsible for skin color. With skin cancer on the rise, the timely identification of skin lesions is crucial for effective treatment. However, the similarity between some skin lesions can result in misclassification, which is a significant problem. It is important to note that benign skin lesions are more prevalent than malignant ones, which can lead to overly cautious algorithms and incorrect results. As a solution, researchers are developing computer-assisted diagnostic tools to detect malignant tumors early. First, a new model based on the combination of “you only look once” (YOLOv5) and “ResNet50” is proposed for melanoma detection with its degree using humans against a machine with 10,000 training images (HAM10000). Second, feature maps integrate gradient change, which allows rapid inference, boosts precision, and reduces the number of hyperparameters in the model, making it smaller. Finally, the current YOLOv5 model is changed to obtain the desired outcomes by adding new classes for dermatoscopic images of typical lesions with pigmented skin. The proposed approach improves melanoma detection with a real-time speed of 0.4 MS of non-maximum suppression (NMS) per image. The performance metrics average is 99.0%, 98.6%, 98.8%, 99.5, 98.3%, and 98.7% for the precision, recall, dice similarity coefficient (DSC), accuracy, mean average precision (MAP) from 0.0 to 0.5, and MAP from 0.5 to 0.95, respectively. Compared to current melanoma detection approaches, the provided approach is more efficient in using deep features. Keywords: skin cancer classification; melanoma detection; you only look once (YOLO); dermatoscopic image analysis; ResNet50 network 1. Introduction The skin is the outermost layer of the human body. The largest organ in the human integument structure comprises multiple layers. It also involves immune cells and cells that generate melanin to keep the body healthy from the carcinogenic potential of ultraviolet radiation [1]. Skin cancer arises when skin cells become disorganized and proliferate uncontrollably, potentially migrating to other body parts. Skin cancer is the most common type of cancer worldwide. Melanoma and non-melanoma pigmented lesions are the two main forms of skin cancer. Melanoma is associated with melanocytes, influencing the color of malignant cells [2]. Diagnostics 2023, 13, 2804. https://doi.org/10.3390/diagnostics13172804 https://www.mdpi.com/journal/diagnostics