About Journal
Computer Vision and Autonomous Systems (CVAS) is an international, peer-reviewed, open-access journal committed to publishing high-quality research, advanced methodologies, and real-world applications in the fields of computer vision, robotics, and autonomous systems. The journal serves as a multidisciplinary platform for researchers, engineers, developers, and industry professionals to share innovative technologies and intelligent solutions that drive autonomy and visual perception in modern systems.
CVAS welcomes original research articles, review papers, case studies, technical notes, and short communications focused on the development, integration, and evaluation of vision-based algorithms, autonomous platforms, sensor fusion techniques, real-time perception, and intelligent decision-making systems.
The journal caters to academic researchers, computer vision scientists, robotics engineers, AI practitioners, and stakeholders interested in cutting-edge advancements and applications in autonomous navigation, machine perception, smart robotics, and intelligent automation.
ISBN: 7386-383X | Publication Frequency : Bi-Monthly
Potential Social Impact
The Journal of Computer Vision and Autonomous Systems (CVAS) holds immense potential to generate meaningful social impact by promoting the responsible advancement of computer vision technologies and autonomous systems across vital sectors. Through the publication of open-access research on real-world applications, the journal fosters the dissemination of transformative solutions in areas such as transportation, robotics, healthcare, smart cities, agriculture, and environmental monitoring. By making high-quality research accessible to a global audience, CVAS empowers innovation in both developed and underrepresented regions, contributing to technological equity and inclusive development. CVAS emphasizes the design and deployment of intelligent visual systems that enhance situational awareness, automate critical processes, and improve safety and operational efficiency across domains. The journal plays a key role in connecting interdisciplinary expertise, bridging the gap between academic exploration and industry-driven implementation.
As a forward-looking platform, CVAS upholds strong ethical principles, promotes transparency, and encourages inclusive research practices, ensuring that the evolution of autonomous technologies aligns with public benefit and sustainable progress.View Articles