Machine Learning Applications in Computer Vision, Data Modeling, and Natural Language Processing

Dear Colleagues,

Over the last several years, the accessibility and availability of massive volumes of data have led to the widespread adoption of machine learning algorithms. Hence, the application of machine learning in industry, healthcare, education, transportation, and food is transforming the world. Among the wide range of research fields advanced by machine learning, computer vision, data modeling, and natural language processing are the most prominent. This can be attributed to their rich background in extracting patterns, supporting decision-making, and interpreting unstructured data, with pivotal importance in different complex applications for autonomous systems, healthcare diagnostics, human–computer interaction, and predictive analytics.

We welcome original contributions to this Special Issue dedicated to exploring the latest developments and innovative applications of machine learning in computer vision (e.g., image classification, object detection and tracking, semantic segmentation, 3D reconstruction, facial recognition); data modeling (e.g., time series forecasting, anomaly detection, generative modeling, feature engineering, clustering and dimensionality reduction); and natural language processing (e.g. information retrieval, information extraction, text classification, text generation, summarization, question answering, machine translation, sentiment analysis).

In this Special Issue, reviews, theoretical and practical research articles, short communications, and letters are welcome. Research areas may include (but are not limited to) the following:

• Supervised learning;
• Multi-instance learning;
• Transductive learning;
• Active learning;
• Meta learning;
• Multitask learning;
• Unsupervised learning;
• Self-supervised learning;
• Constructive learning;
• Association-rule learning;
• Reinforcement learning;
• Forecasting;
• Prediction models;
• Stationary and non-stationary data;
• Linear modeling;
• Deep learning;
• Automated machine learning;
• Language modeling and word embeddings;
• Morphology;
• Parsing;
• Semantics;
• Autonomous systems;
• Human–computer interaction;
• Predictive analytics.

Prof. Dr. Mayra Antonio-Cruz
Prof. Dr. Carlos Alejandro Merlo-Zapata
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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.

• machine learning
• computer vision
• data modeling
• natural language processing
• segmentation
• classification
• object detection
• forecasting
• prediction
• computational linguistics