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Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

“…In this paper, object detection model is developed and implemented with deep learning algorithm. …”
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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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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

“…It introduces techniques for optimizing object detection algorithms, summarizes commonly used object detection datasets and traffic scene datasets, along with evaluation criteria, and performs comparative analysis of the performance of deep learning algorithms. …”
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Smart object detection using deep learning algorithm and jetson nano for blind people by Tan, Mei Yan, Anis Farihan, Mat Raffei, Mohd Arfian, Ismail

“…Therefore, this project develops a smart object detection using deep learning algorithm and jetson nano to improve object detection for blind people. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…This study proposes deep reinforcement learning approaches based on Deep Q-Network to improve multi-objective optimization in recommendation environment and investigated its capability to optimizing precision, novelty, and diversity concurrently. …”
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Object based segmentation and analysis using deep learning algorithm for cats and dogs images by N.Rajandhiran, Shreevishal

“…The deep learning algorithm implemented is the Unet architecture and the Segnet architecture respectively. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

“…This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. …”
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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES by HANIZAM, MOHD HAZIQ NAZMI

“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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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

“…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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Comparison of different deep learning object detection algorithms on fruit drying characterization by Umair, Mohammad Yamin, Norazlianie, Sazali, Kettner, Maurice, Mohd Azraai, Mohd Razman, Weiβ, Robert

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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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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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Classification of Planetary Nebulae through Deep Transfer Learning by Dayang N.F., Awang Iskandar, Zijlstra, Albert A., McDonald, Iain, Rosni, Abdullah, Fuller, Gary A., Ahmad H., Fauzi, Johari, Abdullah

“…We adopted the deep transfer learning approach using three ImageNet pre-trained algorithms. …”
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Multi-objective deep reinforcement learning for recommendation systems by Keat, Ee Yeo, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…The results demonstrated that deep reinforcement learning approaches has superiority performance in MO optimization, and its capability of recommending precise item along with achieving high novelty and diversity against the benchmark that using probabilistic based multi-objective approach based on evolutionary algorithm (PMOEA). …”
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A review of phishing email detection approaches with deep learning algorithm implementation by Nursyafiqah Hazira Mohamad Nazir, Nordaliela Mohd Rusli, Tan, Soo Fun, Chin, K. O.

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License plate detection using deep learning object detection models by Leong, Kar Wan

“…The impact of this project is that it provides informative insights and uncover the potential of the development of real-life applications using recent deep learning object detection models.…”
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Deep learning for face detection using matlab by Slim, Salim Adnan

“…This project report presents face detection using Convolutional Neural Network algorithm and Deep Learning combination (DCT / DL) throughout MATLAB simulation and modeling. …”
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The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Mohd Zamri, Osman, Alanda, Alde, Erianda, Aldo, Shahreen, Kasim, Mohd Faizal, Ab Razak

“…Hence, this paper reports bibliometric analysis used to discover current and future trends and gain new insights into the relationship between deep learning and malware. This paper’s discoveries include: Deployment of deep learning to detect domain generation algorithm (DGA) attacks; Deployment of deep learning to detect malware in Internet of Things (IoT); The rise of adversarial learning and adversarial attack using deep learning; The emergence of Android malware in deep learning; The deployment of transfer learning in malware research; and active authors on deep learning and malware research, including Soman KP, Vinayakumar R, and Zhang Y.…”
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Multiobjective deep reinforcement learning for recommendation systems by Ee, Yeo Keat, Mohd Sharef, Nurfadhlina, Yaakob, Razali, Kasmiran, Khairul Azhar, Marlisah, Erzam, Mustapha, Norwati, Zolkepli, Maslina

“…The results demonstrated that deep reinforcement learning approaches has superiority performance in MO optimization, and its capability of recommending precise item along with achieving high novelty and diversity against the benchmark that using probabilistic based multi-objective approach based on evolutionary algorithm (PMOEA). …”
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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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