Results 31 to 40 of about 259,134 (247)
Watersheds for Semi-Supervised Classification [PDF]
IEEE Signal Processing Letters, 2019 Watershed technique from mathematical morphology (MM) is one of the most widely used operators for image segmentation. Recently watersheds are adapted to edge weighted graphs, allowing for wider applicability. However, a few questions remain to be answered – How do the boundaries of the watershed operator behave?
Aditya Challa +3 more
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Semi-supervised protein classification using cluster kernels [PDF]
Bioinformatics, 2005 AbstractMotivation: Building an accurate protein classification system depends critically upon choosing a good representation of the input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-the-art classification performance.
Weston, J. +5 more
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Ensemble Projection for Semi-supervised Image Classification [PDF]
2013 IEEE International Conference on Computer Vision, 2013 This paper investigates the problem of semi-supervised classification. Unlike previous methods to regularize classifying boundaries with unlabeled data, our method learns a new image representation from all available data (labeled and unlabeled) and performs plain supervised learning with the new feature.
Dengxin Dai, Luc Van Gool
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Semi-supervised Tuning from Temporal Coherence
, 2015 Recent works demonstrated the usefulness of temporal coherence to regularize supervised training or to learn invariant features with deep architectures.
Lomonaco, Vincenzo, Maltoni, Davide
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Semi-supervised Collaborative Text Classification [PDF]
, 2007 Most text categorization methods require text content of documents that is often difficult to obtain. We consider "Collaborative Text Categorization", where each document is represented by the feedback from a large number of users. Our study focuses on the semi-supervised case in which one key challenge is that a significant number of users have not ...
Rong Jin, Ming Wu, Rahul Sukthankar
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Semi-supervised Learning for Photometric Supernova Classification
, 2011 We present a semi-supervised method for photometric supernova typing. Our approach is to first use the nonlinear dimension reduction technique diffusion map to detect structure in a database of supernova light curves and subsequently employ random forest
Breiman +35 more
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Semi-supervised Classification Based Mixed Sampling for Imbalanced Data
Open Physics, 2019 In practical application, there are a large amount of imbalanced data containing only a small number of labeled data. In order to improve the classification performance of this kind of problem, this paper proposes a semi-supervised learning algorithm ...
Zhao Jianhua, Liu Ning
doaj +1 more source
EURASIP Journal on Wireless Communications and Networking, 2020 With the advent of the era of network information, the amount of data in network information is getting larger and larger, and the classification of data becomes particularly important.
Yang Gang +5 more
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A semi-supervised spam mail detector [PDF]
, 2006 This document describes a novel semi-supervised approach to spam classification, which was successful at the ECML/PKDD 2006 spam classification challenge.
Pfahringer, Bernhard
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Bone tumours present significant challenges for affected patients, as multimodal therapy often leads to prolonged physical limitations. This is particularly critical during childhood and adolescence, as it can negatively impact physiological development and psychosocial resilience.
Jennifer Queisser +5 more
wiley +1 more source