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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…A total of 33 variables from each year of the BRFSS dataset were analyzed, incorporating statistical techniques to understand the data and preprocessing methods to prepare it for machine learning. Seven machine learning models—Artificial Neural Network (ANN), Random Forest (RF), Decision Tree (DTT), k-Nearest Neighbors (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Deep Neural Network (DNN)—were used for multi-label classification of the complications. …”
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Industrial datasets with ICS testbed and attack detection using machine learning techniques by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Balla, Asaad, Tahir, Mohammad, Elsheikh, Elfatih A A, Suliman, F M

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An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

“…To achieve this, we measured the performance of three deep learning algorithms for normal and abnormal detection of IDS, and a comparison was made to select the best performance of the deep learning algorithm for detection in IDS, such as RNN, DBN and CNN. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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Intelligent prediction of methane hydrate phase boundary conditions in ionic liquids using deep learning algorithms by Bavoh, Cornelius Borecho, Sambo, Chico, Quainoo, Ato Kwamena, Lal, Bhajan

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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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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach by Dalbouh H.A., Md Norwawi N.

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Design of Modeling Elements of Luoshan Shadow Puppets Creative Goods Based on Deep Learning by Taotao, Xu, Musdi, Shanat, Brendan Chan, Kah Le, Wei, Zhang

“…In this paper, based on the design of modeling elements of mountain shadow puppets, the characteristics of visual elements of shadow puppets creative goods are analyzed, and an intelligent design algorithm of shadow puppets creative goods based on deep learning (DL) is innovatively proposed. …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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An intelligent risk management framework for monitoring vehicular engine health by Rahim, Md. Abdur, Rahman, Md. Arafatur, Rahman, Md. Mustafizur, Zaman, Nafees, Moustafa, Nour, Razzak, Imran

“…The stacked ensemble of the deep learning algorithm outperformed other standard machine learning and deep learning algorithms in providing 80.3% decision accuracy for the 80% training data and efficiently managing large amounts of data. …”
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Rabies Outbreak Prediction Using Deep Learning with Long Short-Term Memory by Abdulrazak Yahya, Saleh, Shahrulnizam, Medang, Ashraf, Osman Ibrahim

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Automated visual defect detection using deep learning by Loh, Xiao

“…Artificial intelligence visual inspection is a technique which utilises computer vision and deep learning technology to mechanically “see” a product and determine whether it has defects, without any human involvement. …”
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A review of object detection in traffic scenes based on deep learning by Zhao, Ruixin, Tang, SaiHong, Supeni, Eris Elianddy, Abdul Rahim, Sharafiz, Fan, Luxin

“…This survey is based on the theory of deep learning. It systematically summarizes the Development and current research status of object detection algorithms, and compare the characteristics, advantages and disadvantages of the two types of algorithms. …”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

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Machine learning and deep learning approaches for cybersecurity: a review by Halbouni, Asmaa Hani, Gunawan, Teddy Surya, Habaebi, Mohamed Hadi, Halbouni, Murad, Kartiwi, Mira, Ahmad, Robiah

“…This paper reviewed intrusion detection systems and discussed what types of learning algorithms machine learning and deep learning are using to protect data from malicious behavior. …”
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Overhead view based person counting using deep learning by Kaw, Chee Zhao

“…However, the counting accuracy of Centroid Tracking algorithm is about 22.2% lower than the DeepSORT tracking algorithm. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…Fortunately, Artificial Intelligence (AI) has recently attracted a lot of attention, and it is now a principal component of these systems. …”
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Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Mohammad, Omar Abdelaziz

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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

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Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification by Wong S.Y., Yap K.S., Zhai Q., Li X.