Search Results - (( pattern using algorithm ) OR ( ((peer learning) OR (deep learning)) algorithm ))

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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Deep learning in face recognition for attendance system: an exploratory study / Mochamad Azkal Azkiya Aziz, Shahrinaz Ismail and Noormadinah Allias by Aziz, Mochamad Azkal Azkiya, Ismail, Shahrinaz, Allias, Noormadinah

“…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 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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Underwater Image Recognition using Machine Learning by Divya, N.K., Manjula, Sanjay Koti, Priyadarshini, S

“…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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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi by Mohd Pauzi, Mohd Farhan

“…Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. A set of children images model captured and then classified into two (2) classes; children and no-children via Convolutional Neural Network (CNN) classifier. …”
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Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi by Rusdinadi, Saffa Nasuha

“…This research contributes to the field of automated infrastructure inspection by integrating Uav technology with advanced deep learning algorithms, presenting a novel approach that reduces manual effort and enhances the accuracy of concrete surface assessments. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…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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Development of spike train algorithms for physiotherapy assessment using deep learning approaches by Nor Rashid, Fadilla' Atyka

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Concrete surface inspection by using Unmanned Aerial Vehicle (UAVs) and deep learning algorithms Yolov7 by Rusdinaidi, Saffa Nasuha, Hashim, Khairil Afendy, Ahmad Dahlan, Zaki

“…These images are then processed using Yolov7, a state-of-the-art object detection algorithm, to accurately identify and classify surface cracks. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks by Roslan, Nurfarah Arina

“…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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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.

“…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…”

An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…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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A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

“…Without human input, these algorithms discover patterns or groupings in the data. …”
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Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network by Md. Ali, Mohd. Adli, Abidin, Mohd Radhwan, Nik Muhamad Affendi, Nik Arsyad, Abdullah, Hafidzul, Rosman, Daaniyal Reesha, Badrud'din, Nu'man, Kemi, Faiz, Hayati, Farid

“…The rapid advancement in pattern recognition via the deep learning method has made it possible to develop an autonomous medical image classification system. …”
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Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

“…Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel by Mohammad Asaduzzaman , Rasel

“…Subsequently, these features are classified using different proposed deep learning models on various publicly available datasets. …”
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Systematic review for phonocardiography classification based on machine learning by Altaf, Abdullah, Mahdin, Hairulnizam, Alive, Awais Mahmood, Ninggal, Mohd Izuan Hafez, Altaf, Abdulrehman, Javid, Irfan

“…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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