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Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil
Published 2024“…This research will focus only on six basic baby sign languages that are commonly used in daily life. The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population
Published 2023“…This study analysed the Phenice method by utilising 3D CT scans by deep learning algorithm for sex estimation and age estimation. …”
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Provider independent cryptographic tools
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Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM
Published 2025“…This study proposes a dual-output deep learning model based on a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, optimized using the Evolutionary Mating Algorithm (EMA). …”
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Predicting user trajectories using deep learning algorithms / Ahmad Zaki Aiman Abdul Rashid, Azita Laily Yusof and Norsuzila Ya’acob
Published 2025“…Next, the performance of the model will be evaluated using regression metrics such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the Coefficient of Determination (R2). …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…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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Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The NARX algorithm is used for the modelling of Hg2+ removal. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Then, the feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. …”
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