Search Results - (( developing implementation developing algorithm ) OR ( learning segmentation using algorithm ))

Brain tumor image segmentation using deep learning approach by Darshan, Suresh

“…In addition, the existing software for brain tumor segmentation are implemented using conventional image segmentation algorithms which are labor intensive and causes over or under segmented tumor regions. …”
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Old Jawi manuscript: Digital recognition / Zaidi Razak by Zaidi, Razak

“…The literature review in this research looks at works conducted in the past on line and character segmentation as well as recognition systems. The information gathered is useful for the development of a line segmentation algorithm, a new character segmentation algorithm, as well as a recognition algorithm which is based on the use of a unique code and Hamming distance calculation. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
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Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani by Ghani, Mazuraini

“…In this project, the suitable method of segmentation is local adaptive threshold. However, the performances of neural network in learning and classification task should be enhanced by redesigning and conducting experiment on other learning algorithm than back-propagation.…”
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Automated visual defect detection using deep learning by Loh, Xiao

“…The main goal of this project is to study and develop various automated defect detection models by utilizing state-of-the-art deep learning segmentation algorithms, including U-Net, Double U-Net, SETR, TransU-Net, TransDAU-Net, CAM and SEAM to perform semantic segmentation in fully supervised and weakly supervised learning manners. …”
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REAL-TIME ILLUMINATION COMPENSATION ON DYNAMIC BACKGROUND FOR CROWD ANALYTIC SURVEILLANCE by MOHAMED AMEEN MASHOOD, MOHAMED ABUL HASSAN

“…The influence of illumination variance has been a major challenge in many background modeling algorithms. Previously developed algorithms which intend to solve this issue produced poor object segmentation or consumed substantial amount of computational time, which made them not implementable at real time. …”
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Deep learning-based water segmentation for autonomous surface vessel by Mohd Adam, Muhammad Ammar, Ibrahim, Ahmad Imran, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus

“…In this work, the deep learning models based on Convolutional Neural Network (CNN) to implement binary semantic segmentation is studied. …”
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Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

“…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

“…Background: This study aims to propose the combinations of image processing and machine learning model to segment the maturity development of the mandibular premolars using a Keras-based deep learning convolutional neural networks (DCNN) model. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…Further, it focuses on the development of various forms of local risk prediction models and simple heart risk scores using non-laboratory features and machine learning (ML) algorithms. …”
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Segmentation Word to Improve Performance Sentiment Analysis for Indonesian Language by Siti Mujilahwati, Siti Mujilahwati, M. Safar, Noor Zuraidin, Supriyanto, Catur

“…Subsequently, sentiment analysis classification testing was conducted using both deep learning and machine learning models to assess data quality and accuracy. …”
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Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning by Jwaid W.M., Al-Hussein Z.S.M., Sabry A.H.

“…The developed U-Net CNN model succeeded in performing the brain tumor segmentation task to classify the input brain images into a tumor or not based on the MRI dataset � 2021, Authors. …”

Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review by Musri, Nabila, Christie, Brenda, Ichwan, Solachuddin Jauhari Arief, Cahyanto, Arief

“…Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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Development of gender and race recognition system using speech and recognition by using frequency spectrum by Ng Siew Fong

“…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

“…The lack of objectivity and standard evaluation criteria in tongue diagnosis have restricted its development. In this project, machine learning algorithm will be applied to design a predictive model for TCM tongue diagnosis. …”
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Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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Analyzing customer reviews for ARBA Travel using sentiment analysis by Abdullah, Nurulain

“…The project entails gathering a dataset of customer reviews from Google Reviews and Facebook, cleaning the text to eliminate any noise, and analyzing sentiments using three machine learning algorithms; Naive Bayes, Support Vector Machine, and Logistic Regression. …”
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Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

“…Moreover, for the proposed SBD algorithm, a comparative study is performed with state-of-the-art algorithms. …”
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