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Object Detection Based on Vision Sensors and Neural Network—2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 128

Special Issue Editors

Department of Computing, Canterbury Christ Church University, Canterbury, UK
Interests: Internet of Things; cyber security; intelligent computing and applications; HCI
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
Machine Learning and Perception Lab, University of Udine, Udine, Italy
Interests: computer vision; machine learning; deep learning; image processing

Special Issue Information

Dear Colleagues,

Object detection has been a research hotspot in computer vision for a long time. Nowadays, it is gaining increasing popularity from the research community and industry with the rapid development and deployment of enabling technologies, such as deep neural networks (DNNs) and high-resolution vision sensors. The past few years have witnessed tremendous successful applications of DNNs and their performance. However, mainstream DNNs tend to become more complex in computation, deeper in network structures, and larger in size in the training datasets. This has created a barrier to employing both data and computationally intensive DNNs on resource-limited vision sensors for applications such as object detection, especially in a timely manner.

This Special Issue looks at object detection from another angle, aiming to solicit state-of-the-art research efforts and works that can be employed to enable object detection in a more lightweight way, considering the resource constraints of vision sensors. The Special Issue includes, but is not limited to, the topics below:

  • Computation-efficient lightweight DNNs;
  • Object detection in data streams;
  • One-shot object detection;
  • Object detection on the move;
  • Edge computing in support of object detection on sensors;
  • Neural network compression techniques;
  • Federated learning for object detection;
  • Bio-inspired sensing technologies;
  • Real-time object detection techniques;
  • New object representation techniques;
  • Swarm learning for object detection in a collective manner;
  • High-performance sensing systems.

Dr. Man Qi
Guest Editor

Dr. Zaira Manigrasso
Guest Editor Assistant

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

  • object detection
  • vision sensing
  • lightweight neural network

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