Journal Menu► ▼ Journal Menu
Journal Browser► ▼ Journal Browser
Special Issue "Computer Vision for Smart Cities"
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 3 July 2023 | Viewed by 2155
Special Issue Editors
Interests: computer vision; deep learning; object detection; visual counting; pedestrian detection; unsupervised domain adaptation; image understanding; artificial intelligence
Interests: CBIR; deep learning; computer vision; transformer networks; abstract reasoning; cross modal; retrieval
Interests: artificial intelligence; deep learning; information retrieval; similarity search; access methods for multimedia information retrieval; wireless sensor networks
Special Issues, Collections and Topics in MDPI journals
Special Issue in Sensors: Convolutional Neural Networks and Edge Computing Application
Special Issue Information
The ubiquity of video surveillance cameras in modern smart cities and the significant development of artificial intelligence (AI) provide new opportunities for the development of applications and services that make life easier for citizens. Like no other sensing mechanism, city camera networks can ’observe’ the physical world, while simultaneously providing visual data to AI systems to extract potentially relevant information from this deluge of data and make/suggest decisions which help to solve many real-world problems where humans are at the epicenter. In this context, many smart applications, especially based on deep learning, have been proposed and are nowadays widely employed worldwide, helping to prevent many criminal activities, to plan infrastructures, and to manage public spaces.
This Special Issue aims to collate original research and review articles on recent advances, technologies, solutions, applications, and new challenges in the field of computer vision for Smart Cities.
Potential topics include, but are not limited to, the following:
- pedestrian detection;
- people tracking;
- parking lot occupancy detection;
- face recognition;
- human activity monitoring;
- person re-identification;
- traffic density estimation;
- crowd counting;
- video violence detection;
- human pose estimation;
- human action recognition;
- personal protective equipment detection;
- facial expression recognition;
- vehicle tracking;
- multi-camera multi-target vehicle tracking.
Dr. Luca Ciampi
Dr. Nicola Messina
Dr. Claudio Gennaro
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. 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 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.
- computer vision
- smart city
- artificial intelligence
- deep learning
- image and video analysis
- smart cameras
- video and image understanding