New Trends in Computer Vision and Image Understanding
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 10 September 2024 | Viewed by 72
Special Issue Editors
Interests: statistical data and signal processing; modeling and simulation; biomedical engineering; machine learning project management
Special Issues, Collections and Topics in MDPI journals
Interests: image understanding; image and video processing; multimedia classification and retrieval; 3D immersive environments; surveillance video applications
Special Issue Information
Dear Colleagues,
Recent advances in deep learning architectures for computer vision and image understanding continue to revolutionize numerous fields, from vehicular technologies to healthcare, through the robotics and automation industries. Building solutions based on current deep learning architectures has been made possible thanks to improved hardware acceleration platforms and the increased availability of rich training datasets from different sensing modalities, such as cameras and LiDAR systems.
These recent advances in vision and image understanding have been successfully applied to complex problems and are creating new opportunities, but due to their computationally intensive nature, they are also bringing significant challenges, including a limited applicability to resource-constrained scenarios and a high environmental footprint.
This Special Issue of the journal Applied Sciences on ‘New Trends in Computer Vision and Image Understanding’ focuses on state-of-the-art contributions from academia and industry in the field of computer vision, with specific interest in image understanding. We invite researchers to submit papers exploring novel deep learning architectures for computer vision and image understanding, new application areas, and novel approaches to deal with existing challenges.
Topics of interest for this Special Issue include, but are not limited to, the following:
- Deep learning;
- 2D/3D Object classification and detection;
- Object detection in adverse conditions;
- Adversarial attack in object detection;
- LIDAR data processing;
- Object tracking;
- Transformers and generative models;
- Scene augmentation and generation;
- Scene analytics;
- Pose estimation;
- Autonomous vehicles;
- Robotics and automation industry;
- Healthcare;
- Edge computing;
- Resource-constrained scenarios;
- Green computing.
Dr. Jesus Requena-Carrión
Dr. Qianni Zhang
Dr. Nikesh Bajaj
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.
Keywords
- computer vision
- image understanding
- object detection and classification
- 2D/3D scene analysis
- image augmentation and generation
- machine learning
- deep learning
- transformers
- vision sensors
- applications
- edge computing
- image annotation
- tracking
