Search Results - (( based detection method algorithm ) OR ( data visualization learning algorithm ))

Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

“…Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri by Pedram , Tabatabaeemoshiri

“…This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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A Hybrid Artificial Intelligence Model for Detecting Keratoconus by Alyasseri Z.A.A., Al-Timemy A.H., Abasi A.K., Lavric A., Mohammed H.J., Takahashi H., Milhomens Filho J.A., Campos M., Hazarbassanov R.M., Yousefi S.

“…This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. …”

Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

“…As a result, the computational cost is reduced in the subsequent stages. Finally, machine learning statistics based on the support vector machine is implemented to detect the cut transitions. …”
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Hybrid sampling and random forest machine learning approach for software detect prediction by Md. Anwar, Hossen, Md. Shariful, Islam, Nurhafizah, Abu Talip, Md. Sakib, Rahman, Fatema, Siddika, Mostafijur, Rahman, Sabira, Khatun, Mohamad Shaiful, Abdul Karim, S. M, Hasan Mahmud

“…The machine learning model is miss leaded by these imbalanced data. …”
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Micro-defects detection on metal screw surfaces based on algorithm of faster region convolutional neural network over internet of things / Nur Aainaa Zainal by Zainal, Nur Aainaa

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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning by Goh, Ching Pang

“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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Application of target detection method based on convolutional neural network in sustainable outdoor education by Yang, Xiaoming, Samsudin, Shamsulariffin, Wang, Yuxuan, Yuan, Yubin, Tengku Kamalden, Tengku Fadilah, Yaakob, Sam Shor Nahar

“…This exploration innovatively proposes a method based on the convolutional neural network (CNN) to mine the target information in underwater camera data. …”
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Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning by Hiu, Theresa Wei Xin

“…In the recent years, computer aided diagnosis method has been employed for the detection and diagnosis of the progression of AD. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

“…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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Identifying suicidal ideation through twitter sentiment analysis using Naïve Bayes / Annasuha Atie Atirah Alias by Alias, Annasuha Atie Atirah

“…By harnessing natural language processing techniques and data visualization tools, the project seeks to provide user-friendly solution for early detection and prevention of suicidal intentions expressed on social media. …”
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Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

A Symbol Recognition System for Single-Line Diagrams Developed Using a Deep-Learning Approach by Bhanbhro, H., Kwang Hooi, Y., Kusakunniran, W., Amur, Z.H.

“…Featured Application: The present study is among the first research efforts to generate augmented datasets of complex single-line diagrams to detect symbols using deep-learning-based algorithms. …”
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Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

“…At the moment, most of the studies on classification of affective states for children focus on visual observations and physiological cues, where all data collection for measuring physiological signals are contact-based and invasive. …”
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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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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

“…Compared to state-of-the-art algorithms and other common methods, our method outperformed them in terms of sensitivity, specificity, and accuracy. …”
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