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Contextual Maximum Entropy Model for Edit Disfluency Detection of Spontaneous Speech [chapter]

Jui-Feng Yeh, Chung-Hsien Wu, Wei-Yen Wu
2006 Lecture Notes in Computer Science  
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

Sheng Gao, Joo-Hwee Lim, Qibin Sun
2007 2007 IEEE International Conference on Image Processing  
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

Farnad Nasirzadeh, Mostafa Mir, Sadiq Hussain, Mohammad Tayarani Darbandy, Abbas Khosravi, Saeid Nahavandi, Brad Aisbett
2020 Sustainability  
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

Sungho Kim
2010 EURASIP Journal on Advances in Signal Processing  
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

Yunhang Shen, Rongrong Ji, Zhiwei Chen, Xiaopeng Hong, Feng Zheng, Jianzhuang Liu, Mingliang Xu, Qi Tian
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
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

Anu Maheshwari, Anjali Dadhich, Dr. Pratistha Mathur
2015 IJARCCE  
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

Md Mahmudur Rahman, Sameer K. Antani, Dinna Demner-Fushman, George R. Thoma, Maria Y. Law, Tessa S. Cook
2014 Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations  
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]

Jiaxi Wu, Jiaxin Chen, Di Huang
2022 arXiv   pre-print
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

Christian Colot, Philippe Baecke, Isabelle Linden
2021 Journal of Big Data  
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]

Xinjie Li, Chun Yang, Songlu Chen, Chao Zhu, Xu-Cheng Yin
2021 arXiv   pre-print
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

Barbara Cardone, Ferdinando Di Martino, Sabrina Senatore
2021 International Journal of Intelligent Systems  
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

T. Wszołek, M. Kłaczyński
2014 Acta Physica Polonica. A  
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

Hongzhen Wang, Ying Wang, Qian Zhang, Shiming Xiang, Chunhong Pan
2017 Remote Sensing  
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

Josef Steinberger, Tomáš Brychcín, Michal Konkol
2014 Proceedings of the 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis  
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

Sangeeta N, Ratnadeep R.
2012 International Journal of Advanced Computer Science and Applications  
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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