The document discusses two topics: face detection techniques and emotional speech recognition. For face detection, it proposes using a joint appearance and shape model with viewpoint and figure-ground mask represented as nodes in a Bayesian network for categorization. Experimental results on Caltech datasets show an accuracy of 97.3% for unsegmented faces. For emotional speech recognition, it explores features, classifiers and experiments recognizing emotions in German and Japanese speech, finding SVMs achieved higher accuracy than other methods.
The document discusses two topics: face detection techniques and emotional speech recognition. For face detection, it proposes using a joint appearance and shape model with viewpoint and figure-ground mask represented as nodes in a Bayesian network for categorization. Experimental results on Caltech datasets show an accuracy of 97.3% for unsegmented faces. For emotional speech recognition, it explores features, classifiers and experiments recognizing emotions in German and Japanese speech, finding SVMs achieved higher accuracy than other methods.
음악 3.0 세대 - 요즘밴드 사례를 중심으로 / Social Media Week SeoulSeungsoon Park
뉴미디어의 등장으로 인해 기존의 음악산업 구조는 크게 변화하였습니다. CD나 TAPE로 음악을 소비하던 음악 1.0시대에서, MP3를 통해 음악을 공유하는 음악 2.0시대를 지나, 이제는 창작자가 직접 소비자에게 음악을 판매하고, 소비자는 음악창작에 직접 참여하는 음악 3.0시대가 펼쳐지고 있습니다. 이러한 변화는 뉴미디어, 즉 ‘소셜네트워크서비스(SNS)’ 및 스마트기기의 등장으로 가능해졌습니다.
소셜네트워크밴드 요즘밴드는 SNS를 통해 사연을 모집하여 음악을 만들고 무료로 배포하는, 국내 최초의 SNS 밴드 입니다. 본 행사에서 요즘밴드가 결성된 배경과, 요즘밴드의 한계를 극복하기 위해 실행한 음악창작 워크숍 사례를 통해, 음악 3.0 시대에 뉴미디어(소셜네트워크 서비스, 스마트기기)를 활용한 음악창작 방식의 새로운 모델을 제안하고자 합니다.
http://socialmediaweek.org/seoul/
Erlang is a functional programming language developed in 1986 by Joe Armstrong for developing distributed and fault-tolerant systems. It emphasizes concurrency, distribution and fault tolerance. Erlang uses lightweight processes instead of threads and supports pattern matching. Its data types include atoms, tuples, and lists. Variables start with uppercase letters while atoms start with lowercase letters. Erlang was released as open source in 1998.
The document compares social media usage and messages on Twitter between South Korea and Japan. Some key differences found:
- South Korean politician websites showed more engagement with the public through information and communication features, while Japanese politicians linked more to other politicians and offline support groups.
- Japanese local governments utilized region-based Twitter portals to automatically categorize and share tweets from local residents and businesses.
- When analyzing tweet categories/hashtags between countries, South Koreans tended to share more information, while Japanese used Twitter for more self-promotion and random thoughts.
음악 3.0 세대 - 요즘밴드 사례를 중심으로 / Social Media Week SeoulSeungsoon Park
뉴미디어의 등장으로 인해 기존의 음악산업 구조는 크게 변화하였습니다. CD나 TAPE로 음악을 소비하던 음악 1.0시대에서, MP3를 통해 음악을 공유하는 음악 2.0시대를 지나, 이제는 창작자가 직접 소비자에게 음악을 판매하고, 소비자는 음악창작에 직접 참여하는 음악 3.0시대가 펼쳐지고 있습니다. 이러한 변화는 뉴미디어, 즉 ‘소셜네트워크서비스(SNS)’ 및 스마트기기의 등장으로 가능해졌습니다.
소셜네트워크밴드 요즘밴드는 SNS를 통해 사연을 모집하여 음악을 만들고 무료로 배포하는, 국내 최초의 SNS 밴드 입니다. 본 행사에서 요즘밴드가 결성된 배경과, 요즘밴드의 한계를 극복하기 위해 실행한 음악창작 워크숍 사례를 통해, 음악 3.0 시대에 뉴미디어(소셜네트워크 서비스, 스마트기기)를 활용한 음악창작 방식의 새로운 모델을 제안하고자 합니다.
http://socialmediaweek.org/seoul/
Erlang is a functional programming language developed in 1986 by Joe Armstrong for developing distributed and fault-tolerant systems. It emphasizes concurrency, distribution and fault tolerance. Erlang uses lightweight processes instead of threads and supports pattern matching. Its data types include atoms, tuples, and lists. Variables start with uppercase letters while atoms start with lowercase letters. Erlang was released as open source in 1998.
The document compares social media usage and messages on Twitter between South Korea and Japan. Some key differences found:
- South Korean politician websites showed more engagement with the public through information and communication features, while Japanese politicians linked more to other politicians and offline support groups.
- Japanese local governments utilized region-based Twitter portals to automatically categorize and share tweets from local residents and businesses.
- When analyzing tweet categories/hashtags between countries, South Koreans tended to share more information, while Japanese used Twitter for more self-promotion and random thoughts.