Call for Papers
Recently, visual contents collected from surveillance cameras, mobile phones, personal photo collections, news footage, or medical images have been explosively increased. How to automatically/quantitatively analyze and understand the acquired visual contents is becoming one of the most active research areas in the vision community due to the scientifically challenging problems and its great benefits to real life applications. On the other hand, machine learning techniques especially the deep learning framework have manifested the surprising superiority for extracting structural and semantic visual representation in numerous computer vision applications such as image classification, object detection/localization, image segmentation, captioning, and so on. With machine learning and computing techniques, it is prospected to discover the inherent structure of the available unconditioned visual contents and to achieve more promising results for various applications based on visual semantic analysis.
This workshop, on Machine Learning and Computing for Visual Semantic Analysis (MLCSA2019) – aims at sharing latest progress and developments, current challenges, and potential applications for exploiting large amounts of visual contents.
Topics
The topics we are interested in, include constructing effective systems to enable visual semantic analysis and building wide applications within the fields of artificial intelligence, machine learning, image processing, ubiquitous computing, data mining, and others.
The sample topics of interest include, but are not limited to, the following: