Connectionists: CFP: Special Issue on Deep Learning in Computer Vision - IET Computer Vision

[Timothy Hospedales]

Call For Papers: Special Issue on Deep Learning in Computer Vision - IET Computer Vision

Aims and Scope 
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 <https://mc.manuscriptcentral.com/iet>. Preparation of the manuscript must follow the IET Guide for Authors <http://digital-library.theiet.org/journals/author-guide>. 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 <mailto:t.hospedales at ed.ac.uk>)
Adriana Romero, Montreal Institute of Learning Algorithms, Canada (adriana.romero.soriano at umontreal.ca <mailto:adriana.romero.soriano at umontreal.ca>)
David Vazquez, Autonomous University of Barcelona & CVC, Spain (dvazquez at cvc.uab.es <mailto:dvazquez at cvc.uab.es>)

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