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Workshop on Machine Learning

22 September 2019

Scope and Motivation

Since 2010, the year of initiation of annual Imagenet Competition where research teams submit programs that classify and detect objects, machine learning has gained significant popularity. In the present age, Machine learning, in particular deep learning, is incredibly powerful to make predictions based on large amounts of available data. There are many applications of machine learning in Computer vision, pattern recognition including Document analysis, Medical image analysis etc. In order to facilitate innovative collaboration and engagement between document analysis community and other research communities like computer vision and images analysis etc. here we plan to organize a workshop of Machine learning before the ICDAR conference.

The topics of interest of this workshop include, but are not limited to:


Important Dates

Submission Deadline: June 07, 2019

Acceptance Notification: July 07, 2019

Camera Ready Papers Due: July 15, 2019

Workshop Date: September 22, 2019

Keynote Speaker

Prof. Yi Yang , Faculty of Engineering and Information Technology,
University of Technology Sydney (UTS), Australia.

Title: Deep neural networks for large-scale video classification and localization

Abstract: Our works mainly focus on the design of deep neural networks to enable the agents with a human-like visual understanding of the world. To leverage video temporal dynamics for complex action recognition, we studied 3D convolutional neural networks for more efficient video classification. We also worked on the interactions between human and object in constrained environments, e.g., kitchen. The videos are ego-centric, containing subtle motion changes. Beyond recognition, we worked on accurate video localization for large-scale clip-level retrieval, which can be applied in many real-world applications, e.g., online video search systems. A more challenging task would be predicting the future from past frames. It requires more sophisticated reasoning and intelligence. To accurately predict future frames, we designed a CubicLSTM for better spatio-temporal modeling. Our works significantly improve the state-of-the-arts in many real-world datasets.

Organizing Committee

General Chairs:

Program Chairs:

Organizing Chair:

Program Committee:

Paper Submission

Paper Submission Instruction

ICDAR-WML 2019 will follow a single blind review process.
Authors may include their names and affiliations in the manuscript.

Paper Format and Length

Papers should be formatted with the style files/details available in the IEEE paper formatting template. Papers accepted for the conference will be allocated 6 pages in the proceedings, with the option of purchasing up to 2 extra pages for AUD 100 per page. This will have to be paid after paper acceptance and at the time of registration. The length of the submitted manuscript should match that intended for final publication. Therefore, if you are unwilling or unable to pay the extra charge you should limit yourself to 6 pages. Otherwise the page limit is 8 pages.

Camera-Ready Website

All camera ready submissions and IEEE copyright form will be handled electronically
via the CPS Website (Link to be provided later).

Paper Submission Link

For paper submission please visit the link https://easychair.org/conferences/?conf=icdarwml2019


For any other information you may contact ICDAR WML 2019 Secretary by email at icdarwml@gmail.com
ICDAR WML 2019 chair by email at umapada_pal@yahoo.com