Search Results - (( initial deep learning algorithm ) OR ( using optimization method algorithm ))

Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. …”
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Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty by Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.

“…The proposed method is assessed using aging data from the NASA battery dataset. …”

Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…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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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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Leveraging transfer learning and label optimization for enhanced traditional Chinese medicine ner performance by Saidah Saad, Zikun, Huang

“…Transfer learning, a novel deep learning method, has shown impressive results in NER tasks. …”
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Wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Alsolai, Hadeel, Gaddah, Abdulbaset, Othman, Mahmoud, Yaseen, Ishfaq, Rizwanullah, Mohammed, Zamani, Abu Sarwar

“…In this aspect, this study develops a new wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning (WSHMSQP-ODL) model. …”
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Design and implementation of a deep learning based hand gesture recognition system for Rehabilitation Internet-Of-Things (RIOT) environments using MediaPipe by Mohd Dhuzuki, Nurul Hanis, Zainuddin, Ahmad Anwar, Kamarul Zaman, Nur Anis Sofea, Ahmad Razmi, Alin Nur Maisarah, Kaitane, Wonderful Shammah, Ahmad Puzi, Asmarani, Johar, Mohd Naqiuddin, Yazid, Maslina, Mohd Nordin, Nor Azlin, Sidek, Shahrul Naim, Mohd Zaki, Hasan Firdaus

“…Future work could incorporate additional deep-learning models like CNNs and RNNs to enhance gesture classification accuracy. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…This proposed classifier achieved 98.2% classification accuracy on the ISIC dataset. These algorithms are proposed while implying modifications to existing statistical, machine, and deep learning methods.…”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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White blood cell recognition for biomarker model using improved convolutional neural network (CNN) by Mohd Safuan, Syadia Nabilah

“…Initially, a transfer learning analysis are conducted using six well known Convolutional Neural Network (CNN) structure which are Alexnet, Googlenet, Densenet, Mobilenet, Resnet and VGG. …”
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Early bacterial detection in bloodstream infection using deep transfer learning algorithm by Son Ali, Akbar, Kamarul Hawari, Ghazali, Habsah, Hasan, Wahyu Sapto, Aji, Yudhana, Anton

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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

“…Choosing a suitable optimization algorithm in deep learning is essential for effective model development as it significantly influences convergence speed, model performance, and the success of the train- ing process. …”
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2TSS: Two-tier semantic segmentation framework with enhancement for hotspot detection of solar photovoltaic thermal images by Nurul Huda, Ishak, Iza Sazanita, Isa, Muhammad Khusairi, Osman, Mohd Shawal, Jadin, Kamarulazhar, Daud, Mohd Zulhamdy, Ab Hamid

“…This research enhances comprehension of multi-tier segmentation architectures in deep learning, focusing on optimizing performance for solar energy systems through comparative analysis of semantic models. …”
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Water wave optimization with deep learning driven smart grid stability prediction by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, Alamgeer, Mohammad, K. Nour, Mohamed, Abdelrahman, Anas, Motwakel, Abdelwahed

“…Recent advancements in Machine Learning (ML) and Deep Learning (DL) models enable the designing of effective stability prediction models in SGs. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…The review coverage includes the initial screening and imaging techniques, image pre-processing, segmentation techniques based on machine learning and deep learning techniques. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…The review coverage includes the initial screening and imaging techniques, image pre-processing, segmentation techniques based on machine learning and deep learning techniques. …”
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Rabies Outbreak Prediction Using Deep Learning with Long Short-Term Memory by Abdulrazak Yahya, Saleh, Shahrulnizam, Medang, Ashraf, Osman Ibrahim

“…The results from this research prove that a deep learning LSTM network can predict the disease prevalence, using the rabies datasets, with a good accuracy. …”
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A framework for Malaysian Sign Language Recognition using deep learning initiatives / Imran Md Jelas by Md Jelas, Imran

“…Later, Long Short-Term Memory (LSTM) artificial neural network (ANN) is proposed as training algorithm in training module and prediction algorithm in detection module to be used for the development of the actual system based on this proposed framework initiative. …”
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Automated cone cut error detection of bitewing images using convolutional neural network by Mohamed Misbahou Mkouboi, Mohamed Moubarak, Olowolayemo, Akeem, Ghazali, Ahmad Badruddin

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Orientation and scale based weights initialization scheme for deep convolutional neural networks by Azizi Abdullah, Wong, En Ting

“…A crucial component in the CNN is the convolution filters which consist of a series of predefined filter weight initialization values. The filter weights are then automatically learned by the neural network throughout the back- propagation training algorithm. …”
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