Search Results - (( pattern based algorithm ) OR ( ((pattern using) OR (deep learning)) algorithm ))
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm
Published 2023“…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
Published 2022“…Prairie Grass experiment database is used as a data to develop toxic gas dispersion prediction model based on deep learning networks. Thus, in this study, development of deep neural network is carried out using MATLAB. …”
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Deep learning in face recognition for attendance system: an exploratory study / Mochamad Azkal Azkiya Aziz, Shahrinaz Ismail and Noormadinah Allias
Published 2022“…The use of deep learning can reach 98 percent accuracy. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
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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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Second, the proposed SPM approach is combined with Deep Belief Network (DBN), called DeepSPM, based on the unsupervised Deep Learning method. …”
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Thesis -
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
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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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
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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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
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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Stereo matching algorithm based on hybrid convolutional neural network and directional intensity difference
Published 2021“…The proposed algorithm contains a deep learning-based method and a handcrafted method. …”
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Glass break detection system using deep auto encoders with fuzzy rules induction algorithm
Published 2019“…This paper proposes a new design of a glass break detection algorithm based on Fuzzy Deep Auto-encoder Neural Network. …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Final Year Project / Dissertation / Thesis -
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Underwater Image Recognition using Machine Learning
Published 2024“…A Convolutional Neural Network (CNN) is a type of a deep learned an algorithm that has been created for image processing when using convolutional layers to automatically and in a hierarchical way learn features from the input images. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…This integration optimizes feature extraction by capturing both spatial and temporal relationships, enhancing the detection of complex network behaviors. Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
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Thesis -
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…Subsequently, these features are classified using different proposed deep learning models on various publicly available datasets. …”
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…In future, the HW-DBN algorithm can be proposed as an integrated deep Learning for the classification performance of attack detection models.…”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…As a solution, the first part of the thesis proposes a novel framework based on Deep Learning (DL) to solve the ambiguities of leaf features that are deemed important for species discrimination. …”
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Conference or Workshop Item -
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Systematic review for phonocardiography classification based on machine learning
Published 2023“…In recent years, machine learning and deep learning techniques have dramatically improved the automation of phonocardiogram classification, making it possible to delve deeper into intricate patterns that were previously difficult to discern. …”
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