DLCV 2017 - Special Issue on Deep Learning in Computer Vision - IET Computer Vision

The goal of IET-CV Special Issue on Deep Learning in Computer Vision is to accelerate the study of deep learning algorithms in computer vision problems.
In 2012, deep learning became a major breakthrough in the computer vision community by outperforming, by a large margin, classical computer vision methods on ILSVRC challenge. Since then, it has been enjoying increasing popularity, growing into a de facto standard and achieving state-of-the-art performance in a large variety of tasks, such as object detection, image captioning and semantic segmentation.
In this special issue, we encourage researchers to formulate original models and potential novel applications of end-to-end vision systems based on deep learning. We are soliciting original contributions or extensions of conference papers that address a wide range of theoretical and practical issues including, but not limited to:
? Large scale image and video understanding with deep models
? Learning with limited data, trends and training strategies
? Supervised learning in computer vision
? Unsupervised feature learning and feature selection
? Generative models
? Attention models and memory networks
? Reinforcement learning
? Model compression for mobile platforms and embedded systems
? Transfer learning
? Industrial and medical applications
? Real time applications
Submission Instructions
Papers should be submitted electronically using the IET ManuscriptCentral. Preparation of the manuscript must follow the IET Guide for Authors. To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important to select SI: Deep Learning in Computer Vision when you reach the “Article Type” step in the submission process.
Important Dates
? Submission deadline: 15th December 2016
? First round decisions: 15th March 2017
? Revisions deadline: 01th May 2017
? Final round decisions: 31th July 2017
? Publication: October 2017
Guest Editors
Timothy Hospedales, University of Edinburgh, UK (t.hospedales-AT-ed.ac.uk)
Adriana Romero, Montreal Institute of Learning Algorithms, Canada (adriana.romero.soriano-AT-umontreal.ca)
David Vazquez, Autonomous University of Barcelona & CVC, Spain (dvazquez-AT-cvc.uab.es)