‌Journal Information

Trends in Computer Vision

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Publishing model:  Open Access

DOI Prefix: 10.62762/TCV

Aims & Scope

Trends in Computer Vision is an international, peer-reviewed academic journal dedicated to publishing high-quality research and advancements in the rapidly evolving field of computer vision. The journal serves as a platform for researchers, practitioners, and industry professionals to share cutting-edge developments, methodologies, and applications that drive innovation and address real-world challenges.

Aims

• To advance fundamental theories, algorithms, and techniques in computer vision.

• To provide a forum for interdisciplinary collaboration between computer vision, artificial intelligence, robotics, healthcare, and other related fields.

• To highlight innovative applications of computer vision across industries, fostering knowledge transfer between academia and industry.

• To identify and explore emerging trends and challenges in the field, promoting novel solutions and breakthroughs.

Scope

The journal covers a broad range of topics in computer vision, including but not limited to:

Core Techniques in Computer Vision

• Image and video understanding

• Object detection, segmentation, and tracking

• Scene reconstruction and 3D vision

• Image classification and feature extraction

• Vision-based generative models

Machine Learning and Visual Representation

• Deep learning for visual recognition

• Transformer architectures for vision tasks

• Weakly supervised, unsupervised, and self-supervised learning

• Few-shot, zero-shot, and transfer learning in computer vision

• Representation learning for multi-scale and multimodal data

Emerging and Interdisciplinary Research

• Vision-language models and multimodal AI

• Computer vision for augmented reality (AR), virtual reality (VR), and mixed reality (MR)

• Biological and cognitive inspirations for vision systems

• Multi-sensor fusion and hybrid visual perception

• Integration of vision with robotics and autonomous systems

Applications and Industrial Innovations

• Autonomous driving and intelligent transportation systems

• Medical image analysis and healthcare diagnostics

• Industrial automation, inspection, and quality control

• Security, surveillance, and facial recognition technologies

• Drone and satellite-based visual analytics

Challenges, Trends, and Ethical Considerations

• Robustness to occlusion, lighting, and scale variations

• Large-scale vision datasets and benchmarking

• Model interpretability, fairness, and explainability

• Energy-efficient and sustainable computer vision techniques

• Ethical issues in visual AI systems, including bias and privacy

Trends in Computer Vision publishes original research articles, review papers, technical notes, and application-driven case studies. The journal welcomes interdisciplinary studies and innovative approaches that address practical challenges, with an emphasis on high-impact and forward-thinking contributions.

Publication Frequency

Quarterly

Ownership

The journal is owned by Institute of Emerging and Computer Engineering.

Archiving

All journals published by IECE are archived in Portico, which provides permanent digital archiving for scholarly journals.

Ethics Statement

IECE is responsible for implementing rigorous peer review and strict ethical policies and standards to ensure that high quality scientific work is added to the field of scholarly publishing. IECE takes such publishing ethics issues very seriously, and our editors are trained to enforce COPE's Core Practices and Guidelines, with a zero-tolerance policy for plagiarism, data falsification, and other behaviours. To verify the originality of content submitted to our journals, we use iThenticate to check submissions against previous publications.