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Improving a tone labeling algorithm for Sesotho
Language Resources and Evaluation, 2014We report on a study that aimed to improve an existing tone label prediction algorithm for Sesotho, an official language of South Africa. Tone is an important prosodic feature of Sesotho, since speakers use tone to distinguish meaning. In order to implement tone in a Text-to-Speech system for Sesotho, a tone modeling algorithm must receive as input the
Mpho Raborife +2 more
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Label confidence based AdaBoost algorithm
2017 International Joint Conference on Neural Networks (IJCNN), 2017AdaBoost is a well-known simple and effective boosting algorithm for classification. It, however, suffers from the overfitting problem in the case of overlapping class distributions and is very sensitive to label noise. To tackle both problems simultaneously, we consider the conditional risk as the modified loss function. This modification leads to two
Zhe Luo, Xin Dang, Yixin Chen 0002
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A multi-label incremental learning algorithm
2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012A multi-label incremental learning algorithm based on hyper ellipsoidal is proposed. To every class, the smallest hyper ellipsoidal that surrounds most samples of the class is structured, which can divide the class samples from others. In the process of incremental learning, only are the hyper ellipsoidals that its class exist in new incremental ...
Yuping Qin +3 more
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Comparisons of sequence labeling algorithms and extensions
Proceedings of the 24th international conference on Machine learning, 2007In this paper, we survey the current state-of-art models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron (AP), Structured SVMs (SVMstruct), Max Margin Markov Networks (M3N), and an integration of search and learning algorithm (SEARN).
Nam Nguyen 0001, Yunsong Guo
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Boundary-labeling algorithms for panorama images
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2011Boundary labeling deals with placing annotations for objects in an image on the boundary of that image. This problem occurs frequently in situations where placing labels directly in the image is impossible or produces too much visual clutter. Previous algorithmic results for boundary labeling consider a single layer of labels along some or all sides of
Andreas Gemsa +2 more
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Lattice labeling algorithms for vector quantization
Proceedings of IEEE International Symposium on Information Theory, 1998Due to its regular structure, lattice vector quantization (VQ) often offers substantial reduction in complexity over conventional VQ. Essentially there are two issues involved in designing a lattice vector quantizer: the development of fast algorithms for lattice decoding, and the construction of efficient algorithms for lattice labeling.
Chun Wang +3 more
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A hierarchical algorithm for image multi-labeling
2010 IEEE International Conference on Image Processing, 2010This paper presents an efficient two-stage method for multi-class image labeling. We first propose a simple label-filtering algorithm (LFA), which can remove most of the irrelevant labels for a query image while the potential labels are maintained. With a small population of potential labels left, we then apply the Naive-Bayes Nearest-Neighbor (NBNN ...
Jiwei Hu, Kin-Man Lam 0001, Guoping Qiu
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An optimization approach to relaxation labelling algorithms
Image and Vision Computing, 1983Abstract It is shown that the relaxation labelling process of Rosenfeld, Hummel and Zucker is a suboptimal minimization of a cost function measuring inconsistency and ambiguity. Two new algorithms which minimize this cost function more efficiently are introduced. Finally, some general comments on relaxation are presented.
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Efficient Parallelization Methods of Labeling Algorithm
2017Digital image processing is a field with broad applications. The development of technology has made it possible to introduce intelligent systems in distinctive areas such as medicine, robotics and astronomy. In this paper, the authors focus on indexing algorithms (also called labeling).
Malgorzata Luchter-Boba +2 more
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Algorithms for realtime component labelling of images
Image and Vision Computing, 1988Abstract Connected component labelling is an important part of identifying regions and performing feature extraction. In a realtime industrial environment where online image analysis is required, it is highly desirable to have a labelling algorithm that can be implemented at pixel rate in parallel with a raster scan of the image.
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