Machine Learning Algorithms for Sensor Data and Image Understanding

Dear Colleagues,

Many contemporary applications of AI, ML and DM are based on datasets collected by a variety of local or remote sensor devices. These application domains cover a huge area of research, from geospatial applications and earth observation to medical prognosis and treatment, from smart devices to smart homes and cities, and so on. In many occasions, the collected datasets require purification, augmentation and several other types of preprocessing before they are suitable for feeding a ML algorithm. Furthermore, the predicted output of the ML algorithm has to be intelligible and useful for humans; therefore, the ML models have to provide human-comprehensible explanations. Finally, since large amounts of the sensor collected datasets are or can be transformed into 2D or 3D images, image processing methods along with methods from AI, ML and DM reinforced with interpretable and explainable capabilities form a new state-of-the-art research domain which covers an enormous area of practical applications.

Dr. Pintelas Panagiotis
Dr. Ioannis E. Livieris
Guest Editors

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