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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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2
Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…Particular attention is given to different loss functions used for training segmentation based on deep learning techniques. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…Particular attention is given to different loss functions used for training segmentation based on deep learning techniques. …”
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4
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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5
Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification
Published 2024“…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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Optimizing high-density aquaculture rotifer Detection using deep learning algorithm
Published 2022“…First, dataset acquisition from digital microscope and manual labelling annotation divided by 60, 20 and 20 percent for training, validation and testing consecutively. Second, is to develop the deep learning algorithm based on YOLOv3. …”
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Proceedings -
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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
Published 2021“…Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. 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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8
Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…This biggest Android Application (App) provides a wide variety of details on requirements such as reviews, quality, number of installs, and explanations for device functionality. This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. …”
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Effective query structuring with ranking using named entity categories for XML retrieval
Published 2016“…Furthermore, it employs Predicates Identification Algorithm (PIA) and Entity Identification Algorithm (EIA) to identify user search intention. …”
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10
Neural network paradigm for classification of defects on PCB
Published 2003“…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…Five benchmark functions are used to accelerate convergence and address the issue of local optima. …”
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Development of gender and race recognition system using speech and recognition by using frequency spectrum
Published 2009“…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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Learning Object -
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Extreme Learning Machine neural networks for multi-agent system in power generation
Published 2023“…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”
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Object based segmentation and analysis using deep learning algorithm for cats and dogs images
Published 2023“…User intervention is constantly required to perform the segmentation. In addition, the algorithms used for the segmentation are conventional rather than modern deep learning techniques which is inevitably more efficient. …”
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Final Year Project / Dissertation / Thesis -
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Brain tumor image segmentation using deep learning approach
Published 2022“…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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Final Year Project / Dissertation / Thesis -
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Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani
Published 2023“…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
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Integration of image processing algorithm and deep learning approaches to monitor ginger plant
Published 2024“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Final Year Project / Dissertation / Thesis -
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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging
Published 2021“…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…This proposed algorithm achieved segmentation accuracy of 96.8% and 92.1% for ISIC and PH2 datasets respectively. …”
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