Search Results - (( java application scheduling algorithm ) OR ( features extraction semantics algorithm ))

Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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Automatic multilevel medical image annotation and retrieval by Mueen, A., Zainuddin, R., Baba, M.S.

“…Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. …”
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Acoustic Profiles Based On Quranic Maqamat Audio Features by Farah Hanim bt Seman @ Abd Jabar

An automatic grading model for semantic complexity of english texts using bidirectional attention-based autoencoder by Chen, Ruo Han, Ng, Boon Sim, Paramasivam, Shamala, Ren, Li

“…This paper first analyzes the importance of automatic classification of semantic complexity in English text, and then builds an autoencoder structure based on bidirectional attention, which captures bidirectional information in text, and then uses the autoencoder structure for feature extraction and dimension reduction, which further strengthens the model’s ability to capture semantic complexity. …”
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Segmentation of pulmonary cavity in lung CT scan for tuberculosis disease by Tan, Zhuoyi, Madzin, Hizmawati, Khalid, Fatimah, Beng, Ng Seng

“…The complexity of pulmonary tuberculosis (TB) lung cavity lesion features significantly increase the cost of semantic segmentation and labelling. …”
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Modelling semantic context for novelty detection in wildlife scenes by Yong, SP, Deng, JD, Purvis, MP

“…Working with wildlife image data, the framework starts with image segmentation, followed by feature extraction and classification of the image blocks extracted from image segments. …”
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Facial image retrieval on semantic features using adaptive mean genetic algorithm by Shnan, Marwan Ali, Rassem, Taha H., Nor Saradatul Akmar, Zulkifli

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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data by Aman, M., Abdulkadir, S.J., Aziz, I.A., Alhussian, H., Ullah, I.

“…The existing topical clustering-based approaches for keyphrase extraction are domain dependent and overlooks semantic similarity between candidate features while extracting the topical phrases. …”
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An object properties filter for multi-modality ontology semantic image retrieval by Sulaiman, Mohd Suffian, Nordin, Sharifalillah, Jamil, Nursuriati

“…Ontology is a semantic technology that provides the possible approach to bridge the issue on semantic gap in image retrieval between low-level visual features and high-level human semantic.The semantic gap occurs when there is a discrepancy between the information that is extracted from visual data and the text description.In other words, there is a difference between the computational representation in machine and human natural language.In this paper, an ontology has been utilized to reduce the semantic gap by developing a multi-modality ontology image retrieval with the enhancement of a retrieval mechanism by using the object properties filter. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

“…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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A deep autoencoder-based representation for Arabic text categorization by El-Alami, Fatima-Zahra, El Mahdaouy, Abdelkader, El Alaoui, Said Ouatik, En-Nahnahi, Noureddine

“…It consisted of three stages: (1) Extracting from Arabic WordNet the most relevant concepts based on feature selection processes (2) Features learning via an unsupervised algorithm for text representation (3) Categorizing text using deep Autoencoder. …”
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Enhanced Deep Learning Framework for Fine-Grained Segmentation of Fashion and Apparel by Usmani, U.A., Happonen, A., Watada, J.

“…We propose a clothing segmentation framework having novel feature extraction and fusion modules. The low-level feature data are extracted by the feature extraction module using Mask Region Convolutional Neural Network (RCNN) segmentation branches and Inception V3 used to extract the high-level semantic data. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Learning a deeply supervised multi-modal RGB-D embedding for semantic scene and object category recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

“…However, extracting discriminative features from multi-modal inputs, such as RGB-D images, in a unified manner is non-trivial given the heterogeneous nature of the modalities. …”
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Semantic focus fusion based on deep learning for deblurring effect by Ismail, .

“…The method is termed semantic focus fusion for deblurring effect. It employs deep learning architecture to extract focus and blurred features. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

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