Collection Overview

Scientific Reports has launched a Guest-Edited Collection on Deep learning for image analysis.

Deep learning for image analysis and object detection is essential enhancing computer vision. It requires state-of-the-art solutions to accurately interpret and identify visual data. These methods employ advanced neural networks to analyse images, detect objects, and extract valuable information, enabling applications in areas such as healthcare, autonomous vehicles, and security. The emphasis for deep learning in image analysis is on creating robust algorithms and models that can manage diverse and complex visual inputs, offering significant improvements in accuracy, efficiency, and real-time processing capabilities.

This will be a Collection of original research papers and will be open for submissions from all authors – on the condition that the manuscripts fall within the scope of the Collection and of Scientific Reports more generally. We are welcoming submissions until 17th April 2026.

Why is this Collection important? 

"This Collection highlights how advanced neural models transform image understanding across science, healthcare, and industry. This topic is timely and impactful as visual data grows exponentially. I’m excited about this Collection for its potential to unite innovative methods in representation learning, robustness, and explainability, driving both theoretical and practical advances. It offers researchers a platform to showcase breakthroughs that shape the future of intelligent image an" - Dr. Yang Xulei

This Collection also supports and amplifies research related to SDG 9 Industry, Innovation & Infrastructure

Why submit to a Collection? 

Collections like this one help promote high-quality science. They are led by Guest Editors, who are experts in their fields, and In-House Editors and are supported by a dedicated team of Commissioning Editors and Managing Editors at Springer Nature. Collection manuscripts typically see higher citations, downloads, and Altmetric scores, and provide a one-stop-shop on a cutting-edge topic of interest. 

Who is involved? 

Guest Editors:

• Qian Jiang, Yunnan University, China
• Nitish Katal, Vellore Institute of Technology Chennai, India
• Xulei Yang, Institute for Infocomm Research (I2R), A*STAR, Singapore

Internal Team:

• In-House Editor: Dr. Thomas Tischer, Scientific Reports, Germany
• Commissioning Editor: Faija Miah, Fully OA Brands, Springer Nature, UK
• Managing Editor: Chantale Davies, Fully OA Brands, Springer Nature, UK

How can I submit my paper? 

Visit the Collection page to find out more about this Collection and how to submit your article.