Evaluation and benchmarking of real-time skin detectors remain challenging because of multiple evaluation attributes that must be considered. Numerous evaluation and benchmarking techniques have been proposed, but they exhibit several limitations. Fixing multiple attributes based on benchmarking approaches by using other attributes limits reliable real-time skin detection. This paper presents comprehensive insights into the evaluation and benchmarking of real-time skin detectors on the basis of two critical directions. Current evaluation criteria highlight conflicting issues and benchmarking techniques to identify weak points, and possible solutions are discussed. The findings are as follows: (1) open issues and challenges to evaluation and benchmarking are emphasized; and (2) decision making using multiple criteria such as reliability, time complexity, and error rate within a dataset is used for evaluating and benchmarking real-time skin detectors to come up with solutions for future .....

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This study aims to develop a new multi-criteria decision analysis methodology for skin detector evaluation and benchmarking based on artificial intelligence models. Two experiments were conducted. The first experiment comprised two stages: (1) Adaptation of the best previous case of skin detection approach utilizes multi-agent learning based on different color spaces. This stage aimed to create a decision matrix of various color spaces, and three groups of criteria (i.e., reliability, time complexity, and error rate within dataset) to test, evaluate and benchmark the adapted skin detection approaches. (2) Performance of multiple evaluation criteria for skin detection engines, this stage included two key stages. First, the correlation between criteria to investigate their relationship and determine their degree of correlation. Second, the performance analysis of criteria to identify the factors that affect the behavior of each criterion. The second experiment utilized a new multi-criter.....

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Objective: This research aims to survey the e®orts of researchers in response to the new and disruptive technology of skin cancer apps, map the research landscape from the literature onto coherent taxonomy, and determine the basic characteristics of this emerging ¯eld. In addition,this research looks at the motivation behind using Smartphone apps in the diagnosis of skin cancer and in health care and the open challenges that impede the utility of this technology. This study o®ers valuable recommendations to improve the acceptance and use of medical apps in the literature. Methods: We conducted a comprehensive survey using the keywords \skin cancer," \apps," and \Smartphone" or \m-Health" in di®erent variations to ¯nd all the relevant articles in three major databases: Web of Science, Science Direct, and IEEE Xplore. These databases broadly cover medical and technical literature. Results: We found 110 articles after a comprehensive survey of the literature. Out of the 110 articles,.....

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