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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Chong, Hou Ming, Yin Yap, Xien, Seng Chia, Kim

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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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. Object classification model is produced through the model training with Deep Neural Networks (DNN). …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Automated visual defect detection using deep learning by Loh, Xiao

“…The main goal of this project is to study and develop various automated defect detection models by utilizing state-of-the-art deep learning segmentation algorithms, including U-Net, Double U-Net, SETR, TransU-Net, TransDAU-Net, CAM and SEAM to perform semantic segmentation in fully supervised and weakly supervised learning manners. …”
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Hand blood vessels pattern recognition by Tan, Xuan Qing

“…This study aimed to address the problem of difficult venous access by proposing a vein feature extraction algorithm for the forearm using transfer learning on a U-net model with EfficientNetB3 as the backbone. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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Deep learning-based water segmentation for autonomous surface vessel by Mohd Adam, Muhammad Ammar, Ibrahim, Ahmad Imran, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus

“…In this work, the deep learning models based on Convolutional Neural Network (CNN) to implement binary semantic segmentation is studied. …”
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Deep learning algorithm and IoT based system for Photovoltaic (PV) defect images classification by Mazlan, Nurul Atikah

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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. In addition, amongst the eighteen TL models evaluated based on the CWT transformation, fourteen was f ound to be able to extract the features reasonable, i.e., VGG16, VGG19, ResNet101, ResNet101 V2, ResNet152, ResNet152 V2, Inception V3, Inception ResNet V2, Xception, MobileNetV2, DenseNet 121, DenseNet 169, NasNetMobile and NasNetLarge. …”
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Implementing BiSM and CCL algorithm for managing audio storage by Hamzah, Hammuzamer Irwan, Low, Tan Jung

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Object detection and classification in marine ecosystem using deep learning neural network / Muhammad Afiq Azman by Azman, Muhammad Afiq

“…The primary objective is to develop and implement artificial intelligence (AI) and machine learning (ML) algorithms tailored to effectively identify within marine ecosystems. …”
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Power allocation with non-orthogonal multiple access for 5G heterogeneous network by Johari, Muhammad Amirul Aiman, Anwar Apandi, Nur Ilyana, Muhammad, Nor Aishah

“…Deep learning can be implemented to improve resource allocation in the context of CoMP by instructing a neural network to predict the optimal power allocation for a specific set of users to resemble the NOMA with HetNet system. …”
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Social learning and principal-agent problems in profit sharing contract by Sapuan N.M., Sanusi N.A., Ismail A.G., Wibowo A.

“…Originality/value -This study is the first of its kind that investigates the implementation of the social learning process in Islamic banking operation. …”

Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR) by Chowdhury Sajadul Islam

“…Upon converting PE files to images, the deep learning pixel-matching algorithm identifies obscured malware features. …”

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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Car dealership web application by Yap, Jheng Khin

“…Hence, two transfer learning algorithms were proposed and implemented to provide initial performance boost to the River adaptive random forest regressor and classifier, respectively. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

“…A pre-trained Efficient DenseNet model has been employed utilizing an extra transition layer in DenseNet-201 to classify the potato leave diseases efficiently. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

“…A pre-trained Efficient DenseNet model has been employed utilizing an extra transition layer in DenseNet-201 to classify the potato leave diseases efficiently. …”
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