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CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Mohd Faizal, Ab Razak

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Improving robotic grasping system using deep learning approach by Mohannad K. H., Farag

“…This research aimed to develop a Deep Learning grasp detection model and a slip detection algorithm and integrating them into one innovative robotic grasping system. …”
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Automated classification radiograph of Periodontal bone loss using deep learning by Al Husaini, Mohammed Abdulla Salim, Habaebi, Mohamed Hadi, Yadav, Seema

“…Several combinations of epochs, learning rates, and optimisation algorithms were tested to enhance performance. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…As a solution, the first part of the thesis proposes a novel framework based on Deep Learning (DL) to solve the ambiguities of leaf features that are deemed important for species discrimination. …”
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ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Khan, Sheroz

“…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

“…The enhancement in error rates proves that the MU-MISO DVB-S2X system with scheduling can be the key solution for DVB-S2X system performance degrada�tion in fading channels, especially rainy fading channels. In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Enhanced faster region-based convolutional neural network for oil palm tree detection by Liu, Xinni

“…Hence, this research aims to close the research gaps by exploring the deep learning-based object detection algorithm and the classical convolutional neural network (CNN) to build an automatic deep learning-based oil palm tree detection and counting framework. …”
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Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

“…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Secure IIoT-enabled industry 4.0 by Zeeshan Hussain, Adnan Akhunzada, Javed Iqbal, Iram Bibi, Abdullah Gani

“…Subsequently, we propose a deep learning (DL)-enabled novel hybrid architecture that can efficiently and timely tackle distributed, multivariant, lethal botnet attacks in industrial IoT. …”
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Digital Transformation Using Industry 4.0 and Artificial Intelligence by Keerthika M., Pragadeesh M., Santhiya M., Jebamalar G.B., Venu H.

“…Machine learning, as well as deep learning, particularly helps in manufacturing, and industries forecast their upkeep requirements and minimize delay. …”