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发布时间:2016-12-23     浏览量:   分享到:

讲座题目一:Image Captioning and Visual Question

讲座时间:9:00-10:00

讲座人Qi Wu 教授

讲座内容简介:

The fields of natural language processing (NLP) and computer vision (CV) have seen great advances in their respective goals of analysing and generating text, and of understanding images and videos. While both fields share a similar set of methods rooted in artificial intelligence and machine learning, they have historically developed separately. Recent years, however, have seen an upsurge of interest in problems that require combination of linguistic and visual information. For example, Image Captioning and Visual Question Answering (VQA) are two important research topics in this area.

In this talk I will first outline some of the most recent progresses, present some theories and techniques for these two Vision-to-Language tasks, and then discuss our recent works. In these works, we first propose a method of incorporating high-level concepts into the successful CNN-RNN approach, and show that it achieves a significant improvement on the state-of-the-art in both image captioning and visual question answering. We further show that the same mechanism can be used to incorporate external knowledge, which is critically important for answering high level visual questions.  Our final model achieves the best reported results on both image captioning and visual question answering on several benchmark datasets.

讲座人简介:

Qi Wu is currently a Senior Research Associate in the Australia Centre for Visual Technology (ACVT) in the University of Adelaide, Australia. He received an MSc in Global Computing and Media Technology, a PhD in Computer Science from the University of Bath (United Kingdom), in 2011 and 2015.  His research interests include cross-depictive style object modelling, object detection and Vision-to-Language problems. He is especially interested in the problem of Image Captioning and Visual Question Answering. His image captioning model produced the best result in the Microsoft COCO Image Captioning Challenges in the last year and his VQA model is the current state-of-the-art in the area. His work has been published in prestigious conferences such as CVPR, ICCV and ECCV.

 

讲座题目二:Radiomics: Process and Development

讲座时间:10:00-11:00

讲座人:Zhiguo Zhou 博士后

讲座内容简介:

Radiomics refers to the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images obtained with PET, CT or MRI. It provides the great potential to capture important phenotypic information, and provides valuable information for personalized therapy. Recently, it has become a hot research topic. In this presentation, the process and challenge of radiomics are presented at first. Then the recent developing method by the author for radiomics is given.

讲座人简介:

Zhiguo Zhou is currently a Postdoctoral Researcher in Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA. He received the B. Eng. and  Ph. D. degrees in computer science and technology from Xidian University, Xian, China, in 2008 and 2014, respectively. He was a Visiting Scholar in Leiden University, Leiden, Netherlands from 2013 to 2014. He has published more than 20 journal and conference papers, including Radiotherapy & OncologyIEEE TSMCInformation ScienceKnowledge-based systemsComputers in Biology and MedicinePattern Recognition and so on. He is also the reviewers for multiple international journals.

His current research interests include Radiomics, Medical Image Analysis, Medical Informatics, Machine Learning, Artificial Intelligence, Evolutionary Computation, Knowledge Representation and Reasoning.