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Browsing Conference Papers by Title

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  • Mu, Y; Xu, M; Yan, S (IEEE Computer Society, 2010-01)
    In this paper we propose Softboost, a novel Boosting al-gorithm which combines the merits of transductive and inductive learning approaches to attack the problem of learning from very few labeled training examples. In the ...
  • Wang, W; Wu, Q; Jia, W; He, S; Yang, J (Springer-Verlag, 2011-01)
    This paper proposes an intelligent system that is capable of automiatically detecting license plates from static images captured by a digital still camera. A supervised learning apporach is used to extract features from ...
  • O'Callaghan, ST; Singh, SP; Alempijevic, A; Ramos, FT (IEEE, 2011-01)
    AbstractObserving human motion patterns is informative for social robots that share the environment with people. This paper presents a methodology to allow a robot to navigate in a complex environment by observing pedestrian ...
  • Peng, Y; Jin, J; Luo, S; Xu, M (ACM, 2010-01)
    Video becomes a crucial information resource in last decades, because of the rapid development of camera as well as the internet explosion. High-quality video sequences are always desired in lots of fields. Since the ...
  • tan, M; Wang, L; Tsang, I (Omnipress, 2010-01)
    A sparse representation of Support Vector Ma- chines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable to each input feature, l0-norm Sparse SVM ...
  • Vidal Calleja, TA; Su, D; De Bruijn, F; Valls Miro, J (IEEE, 2014-05-31)
  • Seah, CW; Tsang, I; Ong, Y; Mao, Q (IEEE, 2012-01)
    In the absence of the labeled samples in a domain referred to as target domain, Domain Adaptation (DA) techniques come in handy. Generally, DA techniques assume there are available source domains that share similar predictive ...
  • Peng, H; Deng, C; An, L; Gao, X; Tao, D (IEEE, 2013-01)
    Content-based video copy detection (CBVCD) has attracted increasing attention in recent years. However, video content description and search efficiency are still two challenges in this domain. To cope with these two problems, ...
  • Fu, B; Wang, Z; Pan, R; Xu, G; Dolog, P (Springer Berlin / Heidelberg, 2012-01)
    There always exists some kind of label dependency in multi- label data. Learning and utilizing those dependencies could improve the learning performance further. Therefore, an approach for multi-label learning is proposed ...
  • Fu, B; Wang, Z; Pan, R; Xu, G; Dolog, P (Springer Berlin / Heidelberg, 2012-01)
    There always exists some kind of label dependency in multi- label data. Learning and utilizing those dependencies could improve the learning performance further. Therefore, an approach for multi-label learning is proposed ...
  • Duan, L; Xu, D; Tsang, I (Omnipress, 2012-01)
    We propose a new learning method for heterogeneous domain adaptation (HDA), in which the data from the source domain and the target domain are represented by heterogeneous features with different dimensions. Using two ...
  • Xu, K; Chen, X; Liu, W; Williams, M (ACM digital library, 2006-01)
    Achieving an effective gait locus for legged robots is a challenging task. It is often done manually in a laborious way due to the lack of research in automatic gait locus planning. Bearing this problem in mind, this article ...
  • Zhao, Y; Bohlscheid, H; Wu, S; Cao, L (IEEE Computer Society Conference Publishing Services (CPS), 2010-01)
    This paper presents a real-world application of data mining techniques to optimise debt recovery in social security. The traditional method of contacting a customer for the purpose of putting in place a debt recovery ...
  • Fu, B; Xu, G; Wang, Z; Cao, L (IEEE, 2013-01)
    Exploiting label dependency is a key challenge in multi-label learning, and current methods solve this problem mainly by training models on the combination of related labels and original features. However, label dependency ...
  • Fu, B; Xu, G; Wang, Z; Cao, L (IEEE, 2013-01)
    Exploiting label dependency is a key challenge in multi-label learning, and current methods solve this problem mainly by training models on the combination of related labels and original features. However, label dependency ...
  • Li, Y; Shen, C; Jia, W; van den Hengel, A (IEEE-Inst Electrical Electronics Engineers Inc, 2013-01-02)
    Finding text in natural images has been a challenging task in vision. At the core of state-of-the-art scene text detection algorithms are a set of text-specific features within extracted regions. In this paper, we attempt ...
  • Sanati, F; Lu, J (IEEE, 2010-01)
    From e-government integration viewpoint, LifeEvent is a collection of actions including at least one public service, which executed in its designated workflow to fulfil request of a citizen arising from a new real-life ...
  • Cui, Z; Zhu, H; Shi, J; Chi, L; Yang, K (IEEE, 2013-01)
    While outsourcing data to cloud, security and efficiency issues should be taken into account. However, it is very challenging to design a secure and efficient mechanism supporting authorization updates. In this paper, we ...
  • Hawryszkiewycz, IT (System Engineering Society, 2010-01)
    Managing engineering projects is becoming more complex especially when projects include networks of organizations. The complexity arises both from the growing number of relationships within a project as well as continual ...
  • Sax, C; Lau, H; Lawrence, EM (IARIA Conference, 2011-01)
    Virtual touchscreen keyboards provide poor text input performance in comparison to physical keyboards, a fact, which can partly be attributed to the weaker tactile feedback, they offer. Users are unable to feel the keys ...