图 书 馆开课单位--南洋理工大学
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11Estimating Camera Pose from a Single Urban Ground-View Omnidirectional Image and a 2D Building Outline Map[估计从一个单一的城市景的全方位图像的摄像机位姿和建筑物二维轮廓图]
Tat-Jen Cham(南洋理工大学) A framework is presented for estimating the pose of a camera based on images extracted from a single omnidirectional image of an urban scene, given a ...
热度：55
Tat-Jen Cham(南洋理工大学) A framework is presented for estimating the pose of a camera based on images extracted from a single omnidirectional image of an urban scene, given a ...
热度：55
12Mining Social Images with Distance Metric Learning for Automated Image Tagging[使用距离度量学习挖掘社交图像以实现自动图像标记]
Steven C. H. Hoi(南洋理工大学) With the popularity of various social media applications, massive social images associated with high quality tags have been made available in many soc...
热度：37
Steven C. H. Hoi(南洋理工大学) With the popularity of various social media applications, massive social images associated with high quality tags have been made available in many soc...
热度：37
13Quality-Aware Collaborative Question Answering: Methods and Evaluation[质量感知的协同问答：方法与评价]
Ee-Peng Lim;Maggy Anastasia Suryanto;Roger Chiang;Aixin Sun(南洋理工大学) Quality-Aware Collaborative Question Answering: Methods and Evaluation
热度：33
Ee-Peng Lim;Maggy Anastasia Suryanto;Roger Chiang;Aixin Sun(南洋理工大学) Quality-Aware Collaborative Question Answering: Methods and Evaluation
热度：33
14Learning to Classify Documents with Only a Small Positive Training Set[学习只用一个小的积极训练集来分类文档]
Xiao-Li Li(南洋理工大学) Learning to Classify Documents with Only a Small Positive Training Set
热度：43
Xiao-Li Li(南洋理工大学) Learning to Classify Documents with Only a Small Positive Training Set
热度：43
15Cascade RSVM in Peer-to-Peer Networks[对等网络中的级联的方法]
Wee Keong Ng;Hock Hee Ang; Vivekanand Gopalkrishnan; Steven C. H. Hoi(南洋理工大学) The goal of distributed learning in P2P networks is to achieve results as close as possible to those from centralized approaches. Learning models of c...
热度：26
Wee Keong Ng;Hock Hee Ang; Vivekanand Gopalkrishnan; Steven C. H. Hoi(南洋理工大学) The goal of distributed learning in P2P networks is to achieve results as close as possible to those from centralized approaches. Learning models of c...
热度：26
16On Stability, Clarity, and Co-occurrence of Self-Tagging[自标记的稳定性、清晰性和共现性]
Aixin Sun; Anwitaman Datta(南洋理工大学) Most studies on tags focus on collaborative tagging systems where each resource (e.g., article, photo) can be tagged by multiple users with multiple t...
热度：98
Aixin Sun; Anwitaman Datta(南洋理工大学) Most studies on tags focus on collaborative tagging systems where each resource (e.g., article, photo) can be tagged by multiple users with multiple t...
热度：98
17Negative Correlations in Collaboration:Concepts and Algorithms[合作中的负相关：概念和算法]
Qian Liu(南洋理工大学) This paper studies efficient mining of negative correlations that pace in collaboration. A collaborating negative correlation is a negative correlatio...
热度：81
Qian Liu(南洋理工大学) This paper studies efficient mining of negative correlations that pace in collaboration. A collaborating negative correlation is a negative correlatio...
热度：81
18Visual Event Recognition in Videos by Learning from Web Data[从web数据学习在视频中的视觉事件识别]
Lixin Duan(南洋理工大学) We propose a visual event recognition framework for consumer domain videos by leveraging a large amount of loosely labeled web videos (e.g., from YouT...
热度：59
Lixin Duan(南洋理工大学) We propose a visual event recognition framework for consumer domain videos by leveraging a large amount of loosely labeled web videos (e.g., from YouT...
热度：59