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A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.] by Wan Xing, Sultan Mohd, Mohd Rizman, Johari, Juliana, Ahmat Ruslan, Fazlina

“…Deep learning-based object detection algorithms can be categorized into three main types: end-to-end algorithms, two-stage algorithms, and one-stage algorithms. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

“…In this paper, an evaluation for these transfer learning to be applied in wafer defect detection. The objective is to establish the best transfer learning algorithms with a known baseline parameter for Wafer Defect Detection. …”
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A Systematic Review Of Machine Learning Algorithms For Mental Health Detection Using Social Media Data by Madina Amiri, Sundresan Perumal, Norita Md. Norwawi, Nurazah Ismail

Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

“…Intrusion Detection System (IDS) is one of the key security components in today’s networking environment. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

“…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

“…Phishing detection is considered a critical problem in cybersecurity, and utilising machine learning with an efficient feature selection method for precisely identifying malicious websites is deemed the most critical challenge. …”
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Cyber-Crime Detection: Experimental Techniques Comparison Analysis by Aljarboua E.F., Bte Md. Din M., Bakar A.A.

“…The objective of this research paper is to conduct experimental techniques comparison analysis for cyber-crime detection by reviewing all possible machine learning algorithms for automatic detection. …”

Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

“…It is a method of extracting second-order statistical texture features to detect diseases more efficiently. Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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Autonomous person-following telepresence robot using monocular camera and deep learning YOLO by Mat Lazim, Izzuddin, Sakri, Ahmad Amin Firdaus, Mauzi, Suffian At-Tsauri, Sahrim, Musab, Ramli, Liyana, Noordin, Aminurrashid

“…This study proposes an autonomous person-following TR using a monocular camera and deep-learning YOLO for person detection and distance estimation. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Performance Analysis of Machine Learning and Deep Learning Architectures on Early Stroke Detection Using Carotid Artery Ultrasound Images by S. Latha, P. Muthu, Khin Wee Lai, Azira Khalil, Samiappan Dhanalakshmi

Autonomous Person-following Telepresence Robot Using Monocular Camera And Deep Learning Yolo by Ahmad Amin Firdaus Sakri, Noor Hanis Izzuddin Mat Lazim, Suffian At-Tsauri Mauzi, Mus’ab Sahrim, Liyana Ramli, Aminurrashid Noordin

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A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces by A. Mostafa, Salama, Ravi, Sharran, Zebari, Dilovan Asaad, Zebari, Nechirvan Asaad, Mohammed, Mazin Abed, Nedoma, Jan, Martinek, Radek, Deveci, Muhammet, Ding, Weiping

“…Addressing these challenges entails an efficient and robust object detection and recognition algorithm. This algorithm can deal with a crowd of multiple faces via a mobile camera carried by a mini drone, and performs realtime video processing. …”
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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission by Gholizadeh, S., Leman, Z., Baharudin, B.T.H.T.

“…SHAP values were used to select AE key features and K-means algorithms were employed to classify damage severity. …”
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A deep learning approach for facial detection in targeted billboard advertising / Lau Sian En by Lau , Sian En

“…Facial detection using deep learning in advertising offers the potential for highly personalised and effective marketing by leveraging real-time consumer demographics. …”
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Comprehensive review of drones collision avoidance schemes: challenges and open issues by Rezaee, Mohammad Reza, Abdul Hamid, Nor Asilah Wati, Hussin, Masnida, Ahmad Zukarnain, Zuriati

“…Additionally, our analysis delves into machine learning techniques, discusses metrics and simulation tools to validate collision avoidance systems, and delineates local and global algorithmic perspectives. …”
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Evaluation of the machine learning classifier in wafer defects classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund

“…In this paper, an evaluation of machine learning classifiers to be applied in wafer defect detection is described. …”
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Vision-Based Hand Detection and Tracking Using Fusion of Kernelized Correlation Filter and Single-Shot Detection by Mohd, Mohd Norzali Haji, Mohd Asaari, Mohd Shahrimie, Ong Lay Ping, Ong Lay Ping, Bakhtiar Affendi Rosdi, Bakhtiar Affendi Rosdi

“…This study explores the use of deep learning techniques for fast and robust hand detection and tracking. …”
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Internet of Things (IoT) applications for estrus detection and management in precision livestock farming: a review by Ashraf, Arselan, Nisa, Syed Qamrun, Ashraf, Afreen, Gunawan, Teddy Surya, Sophian, Ali

“…Recent advancements in the Internet of Things (IoT) have introduced new opportunities to enhance estrus detection through the integration of sensors, data analytics, and machine learning algorithms. …”
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Hybrid sampling and random forest machine learning approach for software detect prediction by Md. Anwar, Hossen, Md. Shariful, Islam, Nurhafizah, Abu Talip, Md. Sakib, Rahman, Fatema, Siddika, Mostafijur, Rahman, Sabira, Khatun, Mohamad Shaiful, Abdul Karim, S. M, Hasan Mahmud

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