Computer Vision and Deep Learning: Advanced Technology and Applications into Civil Engineering
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".
Deadline for manuscript submissions: 20 June 2026 | Viewed by 1214
Special Issue Editors
Interests: applied mathematics; optimization; engineering mechanics; new materials; structural health monitoring; assessments of existing infrastructures; damage identification; resilience of infrastructure; digital twins; BIM integration for management; digital transformation in the construction industry; XR and AR for structures assessments
2. COSNTRUCT, Faculty of Engineering, University of Porto, Porto, Portugal
Interests: railway infrastructures; condition assessment; remote inspection; digital twins; AI; structural health monitoring; digital construction; dynamic testing; drive-by strategies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence is driving a new era in civil engineering. The convergence of computer vision, deep learning, LiDAR, BIM (OPEN-BIM), augmented and extended reality is enabling intelligent solutions that redefine how infrastructure is designed, monitored, and maintained. From automated damage detection and 3D reconstruction to predictive modeling and immersive visualization, these technologies are setting new standards for accuracy, efficiency, and sustainability. This special issue invites cutting-edge research and practical case studies that showcase how AI-powered tools are transforming civil engineering practices. We invite original research articles, reviews, and case studies focusing on novel methods, models, and applications of computer vision and deep learning in civil engineering, that contribute to the advance the state of the art in theory, algorithms, data integration, and real-world implementation.
Topics of interest include, but are not limited to:
- Structural health monitoring and defect detection
- Image-, LiDAR-, and video-based assessment
- BIM integration, digital twins, and AR-assisted applications
- UAV and remote sensing for inspection and mapping
- Deep learning for materials, construction, and asset management
This special issue provides an excellent opportunity for researchers and practitioners to share innovative findings, foster interdisciplinary collaboration, and highlight the pivotal role of AI in building smarter, safer, and more resilient infrastructure systems.
Dr. Hernan Pinto
Dr. Diogo Ribeiro
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 250 words) can be sent to the Editorial Office for assessment.
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.
Keywords
- interoperability
- immersive simulation
- IoT sensors
- 3D visualization
- real-time data
- intelligent automation
- hybrid environments
- spatial contextualization
- predictive analytics
- computer vision and deep learning
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