Search Results - (( developing modality learning algorithm ) OR ( java data normalization algorithm ))
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1
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification
Published 2013“…However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. …”
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3
Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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4
Effect of different modalities of facial images for diagnosis of ASD by deep neural network
Published 2024“…This research aims to explore the potential of various facial image types in diagnosing Autism Spectrum Disorder (ASD) through the application of deep learning neural networks. It delves into how deep learning algorithms perform with different facial image modalities, especially 2D and 3D, while addressing specific challenges associated with each. …”
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Proceeding Paper -
5
SANAsms: Secure short messaging system for secure GSM mobile communication
Published 2008“…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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Conference or Workshop Item -
6
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…To this end, experimental modal analysis of aforesaid structures was carried out by introducing different damage scenarios to generate the modal parameter database. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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10
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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11
A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan
Published 2024“…Meanwhile, in the past decade, the use of haptic technology in autism has increased in terms of various disciplines that can assist in improving their learning skills. Nevertheless, the use of haptic technology in terms of spatial learning is still not fully utilized, and this weakens autistic people in the process of learning about their surroundings. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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13
Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. Furthermore, developing robust and efficient methods are required to handle issues such as orientation and position displacement, sensor fusion and feature incompatibility, automatic feature representation, and how to minimize intra-class similarity and inter-class variability. …”
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14
Computer-assisted pterygium screening system: a review
Published 2022“…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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Dynamics and control of underactuated systems with applications in robotics / Ahmad Azlan Mat Isa … [et al.]
Published 2011“…The goal to study is to develop a model and control methods for underactauted systems. …”
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Research Reports -
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Challenges of hidden data in the unused area two within executable files
Published 2009“…The designed algorithms were intended to help in proposed system aim to hide and retract information (data file) with in unused area 2 of any execution file(exe.file). …”
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Human hearing disorder recognition model using eeg-aep based signal
Published 2022“…This study investigated two conventional machine learning algorithms: support vector machine (SVM) and k-nearest neighbors (KNN), and two deep learning techniques: convolutional neural network (CNN) and improved-VGG16 model. …”
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18
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…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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19
Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi
Published 2023“…The major limitation is the algorithm running speed which can be a little slow when it comes to making recommendations. …”
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20
Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks
Published 2023“…Finally, a hybrid approach of GoogLeNet deep learning algorithm and Convolution Neural Network- Support Vector Machines (CNN-SVM) deep learning is performed to increase the accuracy of tumor classification. …”
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