From Pixels to Perception: Machine Generation of High-Quality Vision and Multi-Modal Data
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (15 July 2025) | Viewed by 468
Special Issue Editors
Interests: image/video restoration; deep learning; compressive sensing
Interests: image/video restoration; image/video understanding; image/video coding
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Leveraging advanced machine learning and deep learning techniques to transform basic pixel information into high-quality visual content and multi-modal data is current research topic of significant interest. This process primarily involves the generation and processing of images, where machines can extract meaningful features from low-level pixel data and then utilize these features for more complex perception tasks. For example, using Generative Adversarial Networks (GANs), machines can not only generate realistic images but also create corresponding visual content based on textual descriptions. Furthermore, by integrating audio and text information, rich multi-modal datasets can be generated. This approach has significant applications across various fields, including computer vision, virtual reality, autonomous driving, and human–computer interaction. Such methods enhance the ability of machines to understand and generate information, providing new momentum for the development of intelligent systems.
High-quality data generation is crucial to the field of electronics, as it significantly enhances the quality and richness of visual content, enabling more immersive and interactive experiences. By integrating these high-quality machine-generated data, this research not only advances the development of multimedia applications but also significantly boosts the academic impact of this journal.
The goal of this Special Issue is to present the recent advances in machine learning/deep learning-based data generation techniques and their applications in intelligent systems. Authors are welcome to submit research papers, as well as literature reviews, related to image/video generation, and their applications in virtual reality and augmented reality, autonomous driving, film production, art and creative design, medical imaging, etc.
We look forward to receiving your contributions.
Dr. Hongping Gan
Dr. Honggang Chen
Guest Editors
Manuscript Submission Information
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Keywords
- image/video generation
- machine learning
- deep learning
- multi-modal data
- virtual reality and augmented reality
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