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  1. 1
    DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES

    DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES by HANIZAM, MOHD HAZIQ NAZMI

    Published 2019
    “…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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  2. 2
    Object based segmentation and analysis using deep learning algorithm for cats and dogs images

    Object based segmentation and analysis using deep learning algorithm for cats and dogs images by N.Rajandhiran, Shreevishal

    Published 2023
    “…The deep learning algorithm implemented is the Unet architecture and the Segnet architecture respectively. …”
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  3. 3
    Mobile machine vision for railway surveillance system using deep learning algorithm

    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

    Published 2021
    “…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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  4. 4
    IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH

    IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH by MOHD YAKOP, SITI HAJAR

    Published 2006
    “…The objective of this project is to develop algorithms inMATLAB and be able to implement image texture analysis by using the developed algorithms. …”
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  5. 5
    Deep learning based emotion recognition for image and video signals: matlab implementation

    Deep learning based emotion recognition for image and video signals: matlab implementation by Ashraf, Arselan, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2021
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  6. 6
    Potential of Metal Artifact Reduction (MAR) and Deep Learning-based Reconstruction (DLR) algorithms integration in CT Metal Artifact Correction: a review

    Potential of Metal Artifact Reduction (MAR) and Deep Learning-based Reconstruction (DLR) algorithms integration in CT Metal Artifact Correction: a review by Mohammed Musta, Njiti, Osman, Noor Diyana, Mansor, Mohd Syahir, Rabaiee, Nor Ain, Abdul Aziz, Mohd Zahri

    Published 2024
    “…However, challenges in implementation and machine learning model reliability require further exploration. …”
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  7. 7
    Brain tumor image segmentation using deep learning approach

    Brain tumor image segmentation using deep learning approach by Darshan, Suresh

    Published 2022
    “…In addition, the existing software for brain tumor segmentation are implemented using conventional image segmentation algorithms which are labor intensive and causes over or under segmented tumor regions. …”
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  8. 8
    An assessment of sedimentation in Terengganu River, Malaysia using satellite imagery

    An assessment of sedimentation in Terengganu River, Malaysia using satellite imagery by Aziz A., Essam Y., Ahmed A.N., Huang Y.F., El-Shafie A.

    Published 2023
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  9. 9
    A review of machine learning in hyperspectral imaging for food safety

    A review of machine learning in hyperspectral imaging for food safety by Mainak Das, Yeo, Wan Sieng, Agus Saptoro

    Published 2025
    “…To address these limitations, advances in non-destructive monitoring techniques with the implementation of machine learning (ML) algorithms can be alternative solutions. …”
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  10. 10
    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm

    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

    Published 2023
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  11. 11
    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…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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  12. 12
    The formulation of a transfer learning pipeline for the classification of the wafer defects

    The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

    Published 2023
    “…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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  13. 13
    Embedded car plate image recognition system

    Embedded car plate image recognition system by Moo Wui Hung

    Published 2008
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  14. 14
    Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification

    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

    Published 2023
    “…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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  15. 15
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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  16. 16
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…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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  17. 17
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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  18. 18
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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  19. 19
    Parallel backpropagation neural network training for face recognition

    Parallel backpropagation neural network training for face recognition by Omarov B., Suliman A., Tsoy A.

    Published 2023
    “…In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. …”
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  20. 20
    Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning

    Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning by Abdulrazak Yahya, Saleh, Ros Ameera, Rosdi

    Published 2023
    “…CNN has long been known for its ability to improve detection and classification in images. With the implementation of deep learning, more deep knowledge can be gathered and help healthcare workers to know more about a patient’s disease. …”
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    Proceeding
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