[Apologies if you receive multiple copies of this e-mail] Dear Colleagues,
Recently, deep learning has triggered a revolution in image processing and computer vision as it allows computational models of multiple layers to learn and represent data by imitating how the brain perceives and understands multimodal information. In recent years, deep learning methods have outperformed conventional machine learning techniques in many application areas including image enhancement, image segmentation, object detection, object recognition, scene understanding, image synthesis, healthcare and visual recognition, among many others. We would like to invite the academic and industrial research community to submit original research as well as review articles to this special issue of the Sensors journal (Impact Factor = 3.031). Topics of interest include: + Learning and Adaptive Sensor Fusion + Multisensor Data Fusion + Emerging Trends in Deep Learning Techniques + Intelligent Measurement Systems + Analysis of Image Sensor Data + Data Augmentation Techniques + Image Classification, Image Clustering, Object Detection, Object Localization, Object Detection, Image Segmentation, Image Compression + Interpolation, Denoising, Deblurring, Dehazing, Inpainting and Super-Resolution + Deep Learning Architectures for Remote Sensing + Image Quality Assessment + Deep Learning-Based Biometrics + Human/Machine Smart Interfaces + Industrial Applications + 3D Point Cloud Measurement and Processing + Image Synthesis Deadline for manuscript submissions: 31 March 2021. For submission details, please visit: https://www.mdpi.com/journal/sensors/special_issues/sens_deep_learn_image_process Guest Editors Prof. Dr. Bogdan Smolka (Silesian University of Technology, Poland) Prof. Dr. M. Emre Celebi (University of Central Arkansas, USA) Prof. Dr. Takahiko Horiuchi (Chiba University, Japan) Prof. Dr. Gianluigi Ciocca (University of Milano-Bicocca, Italy) _______________________________________________ uai mailing list [email protected] https://it.engineering.oregonstate.edu/mailman/listinfo/uai
