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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…This creates the jamming detection and classification parameters. The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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Enhanced android malware detection framework using API application framework layer by Abdul Ghani, Saidah Mastura

“…This thesis was to develop an enhanced framework to detect Android malware application using Application Framework layer components. …”
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Development of obstable avoidance system for 3D robot navigation by Er, Kai Sheng

“…In conclusion, the developed algorithm enables the robot to detect obstacles that are not on the same plane as the 2D LiDAR and cannot be detected using depth camera data.…”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Another structure of MLP trained using backpropagation algorithm is used to detect and locate the base of the young corn tree using the skeleton of the segmented image. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…The K-means algorithm has been around for over a century. …”
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A new intelligent multilayer framework for insider threat detection by Ahmad, Rabiah, Al-Mhiqani, Mohammed Nasser Ahmed, Zainal Abidin, Zaheera, Abdulkareem, Karrar Hameed, Mohammed, Mazin Abed, Gupta, Deepak K., Shankar K.

“…Subsequently, using the K-Nearest Neighbors algorithm, an anomaly insider threat detection algorithm has been developed. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Early tube leak detection system for steam boiler at KEV power plant by Ismail F.B., Singh D., Maisurah N., Musa A.B.B.

802.11 MAC layer sniffer using spoof detection algorithm / Azwan Abdul Satar by Abdul Satar, Azwan

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Face anti-spoofing using Convolutional Neural Networks / Siti Nurul Izzah Bahrain by Bahrain, Siti Nurul Izzah

“…The model included Conv2D and MaxPooling2D layers for feature extraction, followed by a flattened layer and a dense layer with dense, dropout, and batch normalization layers. …”
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Experimenting the dendrite cell algorithm for disease outbreak detection model by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza

“…The characteristics of early outbreak signal which are weak and behaved under uncertainties has brought to the development of outbreak detection model based on dendrite cell algorithm.Although the algorithm is proven can improve detection performance, it relies on several parameters which need to be defined before mining.In this study, the most appropriate parameter setting for outbreak detection using dendrite cell algorithm is examined.The experiment includes four parameters; the number of cell cycle update, the number of dendrite cell allowed to be in population, weight, and migration threshold value. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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Artificial neural network based fast edge detection algorithm for MRI medical images by Gunawan, Teddy Surya, Yaacob, Iza Zayana, Kartiwi, Mira, Ismail, Nanang, Za'bah, Nor Farahidah, Mansor, Hasmah

“…Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. …”
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Distracted driver detection with deep convolution neural networks by Basubeit, Omar Gumaan Saleh

“…This project aims to develop a python algorithm to detect the distracted activities while driving. …”

Real-time power quality disturbance classification using convolutional neural networks by Husodo, Budi Yanto, Dalimi, Rinaldy, Ihsanto, Eko, Gunawan, Teddy Surya

“…Second, an efficient CNN structure was developed to extract unique features. Next, the output of CNNs was then inputted into a fully connected layer with softmax and classification layer to act as the classifier for 29 classes of PQD signals. …”
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Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine by Alemu Lemma, Tamiru, Rangkuti, Chalillullah, Mohd Hashim, Fakhruldin

“…In this paper the result of an attempt to develop a substitute nonlinear model based on multilayer neural network (MLNN) and evolutionary algorithm (EA) for a single-shaft gas turbine having IGVs and VSVs is presented. …”
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Predicting pneumonia and region detection from X-Ray images using deep neural network by Sheikh Md, Hanif Hossain, S M, Raju, Ismail, Amelia Ritahani

“…The algorithm is based on the transfer learning mechanism where pretrained ResNet-50 (Convolutional Neural Network) was used followed by some custom layer for making the prediction. …”
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Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki by Mahmoud, Khaki

“…The results learned from the resistivity survey confirmed the pattern of a continuous structure of layers, as detected from the borehole and geological information. …”
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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review by Musri, Nabila, Christie, Brenda, Ichwan, Solachuddin Jauhari Arief, Cahyanto, Arief

“…Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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Vehicle Detection in Deep Learning by Teoh, Per Nian

“…With the development of computer vision techniques and accessibility of large-scale traffic transport data, deep learning has been enabled to on-road vehicle detection algorithms. …”
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