Application of Computer Vision and Deep Learning in Construction Engineering

Dear Colleagues,

Construction engineering is increasingly benefiting from advancements in computer vision and deep learning technologies, transforming various aspects, such as safety management, quality control, productivity monitoring, and asset management. This Special Issue focuses on innovative research and practical applications leveraging computer vision and deep learning techniques within the domain of construction engineering. We encourage submissions highlighting novel methods, theoretical advancements, experimental studies, and comprehensive reviews addressing challenges and opportunities for integrating these technologies into construction practices. Areas of particular interest include, but are not limited to, automated detection and classification of construction defects, site safety monitoring through image and video analytics, 3D reconstruction and progress monitoring using UAV-based photogrammetry, digital twin creation and management, real-time personnel and equipment tracking, and advanced predictive analytics for project management. Submissions should emphasize both technical developments and practical implications to enhance efficiency, safety, and quality outcomes in construction engineering.

Dr. Seunghyeon Wang
Prof. Sungkon Moon
Guest Editors

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. Applied Sciences 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.