[image 01718] Re: 講演会のお知らせ: 牧 淳人先生 (KTH, Sweden) 3月28日

[Shin'ichi Satoh]

image-mlの皆様、

お騒がせしましてすみません。直前になりましたので再送いたします。ぜひふ
るってご参加ください。

-- Shin'ichi


> image-mlの皆様、
> 
> 国立情報学研究所の佐藤真一です。KTHの牧 淳人先生による以下の講演会のお
> 知らせをお送りいたします。参加無料、参加登録も不要です。どうぞご参加下
> さい。
> 
> -- Shin'ichi
> 
> 
> 日時: 3月28日(月) 16:00-17:00
> 場所: 国立情報学研究所 20階 セミナー室(1)
> http://www.nii.ac.jp/access/
> 
> Title: On the Utility of Generic ConvNets Visual Representations
> 
> Speaker:
> Dr. Atsuto Maki
> Computer Vision and Active Perception Lab (CVAP),
> Royal Institute of Technology (KTH), Sweden
> 
> Abstract:
> We consider the utility of global image descriptors given by Deep
> Convolutional Networks (ConvNets) for visual recognition tasks.  Given
> a ConvNet which has been trained with a large labeled data set, the
> feed-forward units activation at a certain layer can be used as a
> generic representation of a new input image for a target task. We will
> highlight three aspects of this common scenario in the context of
> transfer learning.  We will first visit several factors affecting the
> transferability, including those for learning such as network design
> and distribution of training data as well as post-learning factors
> such as layer choice of the trained ConvNet. By optimising these
> factors, we see that significant improvements can be achieved on
> various standard visual recognition tasks. Then, we will explore what
> information resides in such representations; interestingly we find
> strong spatial information implicit, which was unexpected in a network
> trained for classification problems. We will finally introduce an
> efficient pipeline in an application to visual instance retrieval
> where spatial search is enabled by ConvNet representations. Work
> presented was performed with the computer vision group of CVAP.
> 
> Short Bio:
> Atsuto Maki is a Docent at the Royal Institute of Technology (KTH),
> Sweden. He received the BE degree from Kyoto University, the ME degree
> from the University of Tokyo, and the PhD degree from KTH (in
> 1996). After serving as a researcher at Toshiba Corporate R&D Center,
> a senior researcher at Toshiba Research Cambridge, U.K., and an
> associate professor at Kyoto University, he moved to KTH in 2013. His
> research interests cover a broad range of topics in machine learning
> and computer vision, including motion and object recognition,
> clustering, subspace analysis, stereopsis, and representation
> learning. He is currently a board member of Swedish Society for
> Automated Image Analysis (SSBA).