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Contextual Maximum Entropy Model for Edit Disfluency Detection of Spontaneous Speech
[chapter]
2006
Lecture Notes in Computer Science
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The contextual features contain word-level, chunk-level and sentence-level features for edit disfluency modeling. ...
The Improved Iterative Scaling (IIS) algorithm is employed to estimate the optimal weights in the maximum entropy models. ...
The chunk-level feature is extracted by the mutual information of the word sequence according to co-occurrence and term frequencies of and
Parameter Estimation In maximum entropy modeling, improved ...
doi:10.1007/11939993_60
fatcat:ajjktqpb6fcktmmvoyk7a7astm
Propagating Image-Level Part Statistics to Enhance Object Detection
2007
2007 IEEE International Conference on Image Processing
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Its basic idea is to quantize an image using visual terms and exploit the image-level statistics for classification. ...
Each object is modeled by the parts, each having a Gaussian distribution. The spatial dependency and image-level statistics of parts are modeled through the maximum entropy approach. ...
The concept-by-concept analysis shows that HME improves the detection performance among 87 categories out of the 101 categories, there are 11 categories whose performances become worse, and others have ...
doi:10.1109/icip.2007.4379551
dblp:conf/icip/GaoLS07
fatcat:6zrd5gm63zhfnlvljkt53aw3sm
Physical Fatigue Detection Using Entropy Analysis of Heart Rate Signals
2020
Sustainability
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First, desired features are extracted from the heart signals using different entropies and statistical measures. ...
It can be useful to develop warning systems against high levels of physical fatigue and design better resting times to improve workers' safety. ...
0.0 Mean 0.0 Mean 0.0
Table 8 . 8 The rankings of features in different categories when window length is 125. 125-ASM 125-MMH 125-PSI Feature Name Weight Feature Name Weight Feature Name Weight Log-Energy ...
doi:10.3390/su12072714
fatcat:mewtfqc3trbtjkhpdgwn477h2q
Robust Object Categorization and Segmentation Motivated by Visual Contexts in the Human Visual System
2010
EURASIP Journal on Advances in Signal Processing
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The object category label and figure-ground information are estimated to best describe input images. ...
The main difficulties of visual categorization are two folds: large internal and external variations caused by surface markings and background clutters, respectively. ...
Acknowledgment This research was supported by Yeungnam University research grants in 210-A-054-014. ...
doi:10.1155/2011/101428
fatcat:jkh6t2ymgne6hkad6ptto4jgzu
Noise-Aware Fully Webly Supervised Object Detection
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Such a task, termed as fully webly supervised object detec-* Corresponding author. 1 Code and dataset are available at: https://github.com/ shenyunhang/NA-fWebSOD. ...
Figure 1: The overall flowchart of fully webly supervised object detection. ...
The denominator term JE sums up all the entropies of individual detection scores weighted by their spatial information, i.e., the IoU between two proposals. ...
doi:10.1109/cvpr42600.2020.01134
dblp:conf/cvpr/ShenJCHZLX020
fatcat:x5qvk5mjmvd6bbovidmjn372cm
Opinion Mining: A Survey
IJARCCE - Computer and Communication Engineering
2015
IJARCCE
IJARCCE - Computer and Communication Engineering
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And now Internet has now made it possible to find out the opinions of millions of people on everything from latest gadgets to latest software. ...
In the last few years as the growth & use of Internet increases and share of user's opinions increases, the inspiration towards opinion mining also increases. ...
More future research could be dedicated to all these challenges and more work has to be done for further enhancement of these challenges. ...
doi:10.17148/ijarcce.2015.4140
fatcat:7s7jjvqhhvbetkrdfx2crmdcai
Biomedical image representation and classification using an entropy weighted probabilistic concept feature space
2014
Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations
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This paper presents a novel approach to biomedical image representation for classification by mapping image regions to local concepts and represent images in a weighted entropy based probabilistic feature ...
Furthermore, importance of concepts is measured as Shannon entropy based on pixel values of image patches and used to refine the feature vector to overcome the limitation of the "TF-IDF"based weighting ...
Acknowledgment This research is supported by the Intramural Research Program of the National Institutes of Health (NIH), National Library of Medicine (NLM), and Lister Hill National Center for Biomedical ...
doi:10.1117/12.2043911
fatcat:mz4iznlqp5drjivrevs7u4am44
Entropy-based Active Learning for Object Detection with Progressive Diversity Constraint
[article]
2022
arXiv
pre-print
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Active learning for object detection is more challenging and existing efforts on it are relatively rare. ...
At the first stage, an Entropy-based Non-Maximum Suppression (ENMS) is presented to estimate the uncertainty of every image, which performs NMS according to the entropy in the feature space to remove predictions ...
The basic detection entropy in Eq. ( 2 ) is adopted to quantitively measure the image-level uncertainty from object instances. ...
arXiv:2204.07965v1
fatcat:yjbjfqrcsrfvdd2shbsynevsy4
Leveraging fine-grained mobile data for churn detection through Essence Random Forest
2021
Journal of Big Data
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In addition, compared to Random Forest and Extremely Randomized Trees, Essence Random Forest better leverages the value of unstructured data by offering an enhanced churn detection regardless of the addressed ...
Then, we show that, on the short term, these alternative fine-grained data might complement the communication network for an improved churn detection. ...
Churn % of people visiting same url level3 weighted by
contribution to individual total pages viewed
Table 3 3 Service metrics Feature
Label
Entropy duration of service visits-level 1
Entropy ...
doi:10.1186/s40537-021-00451-9
fatcat:4mg4lllwbnemfkkuxmjulgd4zy
Semantic Bilinear Pooling for Fine-Grained Recognition
[article]
2021
arXiv
pre-print
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Specifically, we design a generalized cross-entropy loss for the training of the proposed framework to fully exploit the semantic priors via considering the relevance between adjacent levels and enlarge ...
., vehicle identification or bird classification, has specific hierarchical labels, where fine categories are always harder to be classified than coarse categories. ...
ACKNOWLEDGMENT This work was partly supported by National Natural Science Foundation of China (61703039 and 62072032), Beijing Natural Science Foundation (4194084 and 4174095) and Fundamental Research ...
arXiv:1904.01893v4
fatcat:26zwq6immzbmpnmowttdxnjycq
Improving the emotion‐based classification by exploiting the fuzzy entropy in FCM clustering
2021
International Journal of Intelligent Systems
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An entropy-based weighted version of the fuzzy c-means (FCM) clustering algorithm, called EwFCM, to classify the data collected from streams has been proposed, improved by a fuzzy entropy method for the ...
Emotion detection in the natural language text has drawn the attention of several scientific communities as well as commercial/marketing companies: analyzing human feelings expressed in the opinions and ...
ACKNOWLEDGMENTS Open access funding provided by Universita degli Studi di Napoli Federico II within the CRUI-CARE Agreement. ...
doi:10.1002/int.22575
fatcat:iclkx7ibqbb5zbgc5lvnednzfu
Automatic Detection of Long-Term Audible Noise Indices from Corona Phenomena on UHV AC Power Lines
2014
Acta Physica Polonica. A
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Selected and properly ltered samples provided the basis for calculations of long-term noise indicators. ...
A combined selection of distinctive features of CAN is necessary in order to distinguish the actual signal from the external interference. ...
Acknowledgments The paper has been written and the respective research work undertaken within the project 2011/01/D/ST6/07178 (National Science Centre). ...
doi:10.12693/aphyspola.125.a-93
fatcat:ctzjt66ipbduvjniixd6rcjcju
Gated Convolutional Neural Network for Semantic Segmentation in High-Resolution Images
2017
Remote Sensing
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The gate is implemented by the entropy maps, which are generated to assign adaptive weights to different feature maps as their relative importance. ...
Specifically, we explore the relationship between the information entropy of the feature maps and the label-error map, and then a gate mechanism is embedded to integrate the feature maps more effectively ...
Then the generated entropy heat map is treated as the input weight (pixel-to-pixel) of the low-level feature maps when merged with high-level feature maps. ...
doi:10.3390/rs9050446
fatcat:vzn4bjyogrbrlbeh7xak24lkma
Aspect-Level Sentiment Analysis in Czech
2014
Proceedings of the 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
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We annotated the corpus with two variants of aspect-level sentiment -aspect terms and aspect categories. ...
Our system detects the aspect terms with Fmeasure 68.65% and their polarities with accuracy 66.27%. The categories are recognized with F-measure 74.02% and their polarities with accuracy 66.61%. ...
.1.05/1.1.00/02.0090, and by project MediaGist, EU's FP7 People Programme (Marie Curie Actions), no 630786. ...
doi:10.3115/v1/w14-2605
dblp:conf/wassa/SteinbergerBK14
fatcat:litdkwfeknbvdlk4r3unajszsy
Hybrid Feature Extraction Technique for Face Recognition
2012
International Journal of Advanced Computer Science and Applications
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The proposed method uses hybrid feature extraction techniques such as Chi square and entropy are combined together. Feed forward and self-organizing neural network are used for classification. ...
We evaluate proposed method using FACE94 and ORL database and achieved better performance. ...
. Obtain hybrid features from face by combining values of Chi Square test and Entropy together. ...
doi:10.14569/ijacsa.2012.030210
fatcat:42yalnlrunahfazdxyot4f5qce
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