Search Results - (( java simulation optimization algorithm ) OR ( quality deep learning algorithm ))

A systematic literature review of deep learning neural network for time series air quality forecasting by Zaini N., Ean L.W., Ahmed A.N., Malek M.A.

“…air quality; algorithm; artificial neural network; industrial development; literature review; machine learning; public health; time series; urbanization; air pollution; forecasting; human; time factor; Air Pollution; Deep Learning; Forecasting; Humans; Neural Networks, Computer; Time Factors…”

Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…In the performance comparison between proposed deep reinforcement learning with evolutionary algorithm, despite one of the variants of evolutionary algorithm has good performance in precision, it has rather weak performance in term of novelty and diversity. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…The study then proposes a stacked ensemble deep learning framework for a faster and more efficient water quality analysis. …”
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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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Light weight deep learning algorithm for voice call quality of services (Qos) in cellular communication by Ramalingam, Mritha, Sultanuddin, S. J., Nithya, N., Raj, T. F. Michael, Kumar, T. Rajesh, Prasad, S. J. Suji, Al-Ammar, Essam A., Siddique, M. H., Udayakumar, Sridhar

“…In this paper, a deep learning algorithm was proposed to ensure the voice call quality of the cellular communication networks. …”
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Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Development of deep learning based user-friendly interface for fruit quality detection by Mohd Ali, Maimunah, Hashim, Norhashila

“…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
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A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction by Wen Yee Wong, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Sarah Abdul Razak, Hanee Farzana Hizaddin, Mohd Istajib Mokhtar, Muhammad Mokhzaini Azizan

Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa by Mawada Mohamed , Nour El Daim El Khalifa

“…Meanwhile, in recent years, Deep Learning algorithms for Sentiment Analysis has emerged as one of the most popular algorithms, which provides automatic feature extraction, rich representation capabilities, and better performance than most of the traditional learning algorithms. …”
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…Recent advances in deep learning techniques, based on universal approximation theorem of neural network seems promising to tackle the high dimensional problem. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

Underwater Image Recognition using Machine Learning by Divya, N.K., Manjula, Sanjay Koti, Priyadarshini, S

“…A Convolutional Neural Network (CNN) is a type of a deep learned an algorithm that has been created for image processing when using convolutional layers to automatically and in a hierarchical way learn features from the input images. …”
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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

“…The simulation is implemented with iFogSim and java programming language. …”
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Video Surveillance Image Enhancement Using Deep Learning by Aminudin, Muhamad Faris Che

“…There are two deep learning blocks which are Deep Learning Block 1 and Deep Learning Block2 (DLB1 and DLB2) and image fusion in the proposed DLIE model. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

“…A step towards long network performance optimization is theterm use of deep reinforcement learning (DRL), which can learn the best policy via interaction with the environment. …”
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Gender classification based on asian faces using deep learning by Janahiraman T.V., Subramaniam P.

The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Ji, Xueyan, Samsudin, Shamsulariffin, Hassan, Muhammad Zarif, Farizan, Noor Hamzani, Yuan, Yubin, Chen, Wang

“…This study intends to develop a Spatial Temporal-Graph Convolutional Network (ST-GCN) action detection algorithm based on the MediaPipe framework. This is achieved by integrating deep learning and artificial intelligence technologies. …”
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Multiobjective deep reinforcement learning for recommendation systems by Ee, Yeo Keat, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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