Dear Colleagues,

Recent advancements in machine learning have driven researchers and the industry to progressively integrate neural networks into an abundance of applications in domains such as media, healthcare, security, banking or retail. The power of deep neural networks is situated in their predicting efficiency and adaptability to diverse circumstances, depending on their specific demands and available resources. Despite the capabilities of artificial intelligence models, they are often designed and tested upon unstructured data, i.e., uncorrelated data in terms of contextual comprehension. Although a trained neural network is capable of distinguishing different objects even when there is no prior information about them, delving into further information on how these objects relate to each other under the scope of a specific context requires further tuning. For example, a company’s chatbot engine can provide useful information about a client’s request based on the provided keywords; however, the customer may use words or expressions with ambivalent meaning, resulting in a failed sentiment estimation, if not examined under context.

Semantic analysis enables researchers and corporations to extract additional information from unstructured data by exploiting the machine learning predictive capabilities. In retail, semantic analysis aims at providing better decision-making for organizations and superior customer experience. In image and video applications, semantic analysis is useful in numerous occasions of human–computer interaction, such as smart surveillance or autonomous driving, in the form of scene recognition.

This Special Issue is addressed to high quality, state-of-the-art research papers that deal with neural networks in semantic analysis. We solicit original papers of unpublished and completed research that are not currently under review by any other conference/magazine/journal. Topics of interest include but are not limited to the list below:

• Explainable AI
• Human-In-The-Loop
• Scene Recognition
• Affective Computing
• Semantic Classification and Clustering
• Medical Imaging Segmentation
• Autonomous Cars
• Smart Surveillance
• Recommendation Systems

Dr. Nicholas Vretos
Dr. Dimitrios Zarpalas
Prof. Dr. Yitzhak Yitzhaky
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.