Deep Learning-Based Image Processing, Analysis and Reconstruction Technology

Dear Colleagues,

This Special Issue of Applied Sciences, “Deep Learning-Based Image Processing, Analysis and Reconstruction Technology”, examines how deep learning is fundamentally transforming the processing, interpretation, and reconstruction of sensor-derived image data. Recent advances in convolutional neural networks, generative models, flow and diffusion models, and transformer-based architectures have enabled unprecedented accuracy, efficiency, and robustness across diverse applications, including medical imaging, remote sensing, autonomous vehicles, augmented reality, and industrial inspection.

We invite contributions addressing—but not limited to—the following topics: image denoising and super-resolution, semantic segmentation and object detection, anomaly detection in sensor imagery, three-dimensional reconstruction from multi-view or depth data, and the fusion of multi-modality sensor inputs (e.g., LiDAR + camera, multispectral + RGB).

Submissions may present theoretical or applied research, encompassing algorithm development, system integration, case studies, and novel datasets. Our objective is to showcase transformative work that demonstrates how deep learning enhances the performance, reliability, and usability of sensor-based imaging systems.

Prof. Dr. Suk-Ho Lee
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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.