Search Results - (( parameter optimization method algorithm ) OR ( features extraction semantics algorithm ))

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Facial image retrieval on semantic features using adaptive mean genetic algorithm by Shnan, Marwan Ali, Rassem, Taha H., Nor Saradatul Akmar, Zulkifli

Get full text
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

“…Further manual inspection during the experiments suggested that by using complete word and syntactical features or combination of these features with other features such as the semantic feature, would yield an improved result.…”
Get full text
Get full text

Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
Get full text
Get full text

Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
Get full text
Get full text
Get full text

Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
Get full text
Get full text

Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
Get full text
Get full text

Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
Get full text
Get full text

Multi-level of feature extraction and classification for X-Ray medical image by Abdulrazaq, M, Alshaikhli, Imad Fakhri Taha, Mohd Noah, Shahrul Azman, Fadhil,, Moayad Al Athami

“…Specifically, this study proposed pertinent feature extraction algorithm for X-ray medical images and determined machine learning methods for automatic X-ray medical image classification. …”
Get full text
Get full text
Get full text
Get full text