[PDF] Top 20 Automatic Characterization of Exploitable Faults: A Machine Learning Approach
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Automatic Characterization of Exploitable Faults: A Machine Learning Approach
... of learning performs majority voting among the decisions of the constituent weak learners (decision trees in the present context) to determine the class of the ...proposed approach is reminiscent of ... See full document
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Comparing a Hand crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation
... The automatic evaluation of machine translation (MT) has proven to be a very significant research ...Most automatic evaluation methods focus on the evalua- tion of the output of MT as they compute ... See full document
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Category Based Automatic Classification Of Online News Articles Using Machine Learning
... categories. Automatic text classification needed because there is a quick increase in these numbers of machine-readable ...supervised learning task whose aim is to classify the unlabeled documents ... See full document
9
Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach
... Random forests can be used as an unsupervised tech- nique. This approach involves the generation of a synthetic dataset to represent data without dependence. The synthetic dataset is appended to the original one, ... See full document
11
An Approach for Concept-based Automatic Multi-Document Summarization using Machine Learning
... Natural Language Processing (NLP) is an area of research and application that analyze how computers are used for understanding and manipulating natural language text or speech to achieve the desired tasks. The goal of ... See full document
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A Machine Learning Approach to Automatic Functor Assignment in the Prague Dependency Treebank
... An important feature of C5.0 is its mechanism to con- vert trees into collections of rules called rulesets. Rulesets are generally easier to understand than trees since each rule describes a specific context associated ... See full document
8
Machine learning driven non-invasive approach of water content estimation in living plant leaves using terahertz waves
... non-invasive machine learning (ML) driven approach using terahertz waves with a swissto12 material characterization kit (MCK) in the frequency range of ...different machine ... See full document
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A Machine Learning Approach to Sentence Ordering for Multidocument Summarization and Its Evaluation
... MDS is the task of generating a human readable summary from a given set of documents. With the increasing amount of texts available in electronic format, automatic text summarization has become necessary. It can ... See full document
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Automatic face image annotation using machine learning techniques
... D. Classification: After the face is detected, it has to be classified based on gender and age. There are various methods used to classify the human faces. An experiment was carried out, (Malkarthekar et al., 2009) where ... See full document
6
A Machine Learning Approach to Automatic Term Extraction using a Rich Feature Set
... speech - POS) knowledge to more sophisticated hy- brid knowledge, such as the analysis of the term context. As far as we know, the combined use of this specific knowledge has not been applied before. Another difference ... See full document
8
Automatic Detection of Spring Faults During Assembly of Reciprocating Compressors
... mechanical faults can occur due to production and assembly intolerances, or due to material ...such faults in order to prevent end users receiving such ...increase machine reliability and decrease ... See full document
11
A Machine Learning Approach to Convert CCGbank to Penn Treebank
... Matsuzaki, T. and Tsujii, J. (2008). Comparative parser performance analysis across grammar frameworks through automatic tree conversion using synchronous grammars. In Proceedings of the 22nd International ... See full document
8
Automatic Differentiation in Machine Learning: a Survey
... deep learning techniques (Goldberg, 2016), with applications in tasks including machine translation (Bahdanau et ...deep learning approaches, statistical models in NLP are commonly trained using ... See full document
43
A Machine Learning Approach for Phenotype Name Recognition
... A large amount of biomedical knowledge is available in the biomedical literature. So, automatic processing of biomedical literature to capture and formalize this embedded information is very demanding. Current ... See full document
16
Automatic Gathering of Labeled Images Using a Web Crawler to Facilitate Automotive Machine Learning
... for machine learning is time consuming. We built an efficient machine-learning system and automated data ...facilitate machine learning of automotive applications by local ... See full document
5
A Machine Learning Approach to Automatic Music Genre Classification
... chine learning is used to accomplish the AMGC ...homogeneous approach, that is, the very same classifier is employed as individual component classifier in each music ...Vector Machine classi- fier (SVM) ... See full document
12
Diagnosis of series DC arc faults - a machine learning approach
... Fig. 2 outlines the method of the proposed IntelArc system. The system utilizes a framework of trained HMM relating to different network conditions. Features are extracted from win- dows of network current data and ... See full document
12
A Machine Learning Approach to the Automatic Evaluation of Machine Translation
... a machine learning approach to evaluating the well- formedness of output of a machine translation system, using classifiers that learn to distinguish human reference translations from ... See full document
8
A machine learning approach to the automatic classification of female uroflowmetry measurements
... of machine learning algorithms out of which the user can ...chine learning algorithm to get higher cross val- idation ...specific machine learning algorithm that must be used for a ... See full document
29
Review on the Methods of Automatic Liver Segmentation from Abdominal Images
... The gray level based methods directly utilize image’s features. They are the main methods used in clinical practice, especially in tumour segmentation. However, these methods rely heavily on the evaluation of the gray ... See full document
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