Applications of Artificial Intelligence in Analysis and Recognition of Handwritten Document Images

Dear Colleagues,

We are inviting submissions to the Special Issue on Applications of Artificial Intelligence in Analysis and Recognition of Handwritten Document Images.

The analysis and recognition of handwritten documents present distinct challenges that have garnered increased attention in recent years. With the growing volume of digitized handwritten content, there is considerable demand in developing and applying advanced techniques and methodologies to enhance the efficiency and accuracy of handwritten document processing. Within this context, the detection, segmentation, and recognition of handwritten digits and texts, writer identification, and other problems related to handwritten documents have become important for the research community. Therefore, to alleviate human efforts and enhance computational efficiency, computational intelligence systems play an important role in addressing complex problems associated with handwritten document analysis. These systems leverage various artificial intelligence techniques, including neural networks, support vector machines, deep learning, and evolutionary algorithms. In some cases, a hybrid approach that combines multiple techniques may be essential to effectively address the intricacies of a given problem.

This Special Issue provides an opportunity for researchers to tackle the broad challenges in both the theoretical and application aspects of artificial intelligence in the analysis and recognition of handwritten documents. The objective is to bring together experts and practitioners to delve into innovative ideas, methodologies, and advancements in this field. We encourage researchers to contribute original research articles and review papers that address the Special Issue on "Applications of Artificial Intelligence in Analysis and Recognition of Handwritten Document Images". Topics of interest include, but are not limited to, the following aspects:

• Optical character recognition (OCR) for handwritten documents.
• Detection, segmentation, and recognition of handwritten digits.
• Detection, segmentation, and recognition of handwritten text.
• Feature extraction and representation in handwritten document analysis.
• Writer identification and verification in handwritten content.
• Handwritten digit and text dataset (e.g., Latin, Arabic, Chinese).
• Handwriting style transfer.
• Handwritten document understanding.
• Artificial intelligence for handwritten document analysis.
• Binarization of handwritten document image.
• Handwritten document analysis using artificial intelligence methods.
• Anomaly detection in document images.
• Document layout analysis for handwritten materials.
• Deep learning approaches for handwritten document analysis.
• Application of generative AI in handwritten document images.
• Explainable artificial intelligence in handwritten document images.
• Applications of handwritten document analysis in real-world scenarios.
• Hybrid systems combining multiple techniques for improved recognition.
• Application of large language models in handwritten document analysis.
• Word spotting in handwritten document images.
• Machine learning applications in handwritten document images.
• Script recognition.
• Text line extraction.

Dr. Hüseyin Kusetogullari
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Electronics 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 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.

• handwritten document images
• recognition
• detection
• segmentation
• artificial intelligence