Search Results - (( user evaluation method algorithm ) OR ( images classification _ algorithm ))

Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…All algorithms showed more stability and accuracy when training size applied is more than 6% by the Equal Sample Rate (ESR) method with six variables. …”
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Leaf condition analysis using convolutional neural network and vision transformer by Yong, Wai Chun, Ng, Kok Why, Haw, Su Cheng, Naveen, Palanichamy, Ng, Seng Beng

“…Through the use of a hybrid deep learning model that combines vision transformer and convolutional neural networks for classification, the algorithm can be optimized. The model performance is evaluated and compared with the other methods to ensure quality and usage compatibility in the plantation domain. …”
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Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

“…At present, the email is submerged with spam content, both in text-based form or undesired text planted inside the images. This study reviews articles on phishing image spam classification published from 2006 to 2020 based on spam classification application domains, datasets, features sets, spam classification methods, and the measurement metrics adopted in the existing studies. …”
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A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid by Saari, Mohamad Shahmil, Md Nor, Romiza, Huzaifah, A Hamid

“…Furthermore, the accuracy of the image classification can be improved by increasing the number of datasets, the distance of images from the camera, and the labelling process. …”
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Automated pavement imaging program (APIP) for pavement cracks classification and quantification – a photogrammetric approach by Mustaffar, Mushairry, Puan, O. C., Ling, Tung Chai

“…The algorithms developed in this study are found to be capable of identifying type of cracking and its severity level with an accuracy of about 90% when compared to the traditional method. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language by Sutarman, .

“…Thus by adding processes before classification methods such as feature selection methods can provide better data input in the classification process, it is expected to improve the performance of the method of classification. …”
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Malay festive seasons food recognition for calorie detection / Nurul Hafiza Basiruddin by Basiruddin, Nurul Hafiza

“…Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification which is the part of the Support Vector Machine (SVM) algorithm. …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz by Abd Aziz, Nur Hasyimah

“…CNN was chosen as an algorithm for classification task because various studies had concluded that it is able to produce highly accurate result. …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

“…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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Malay festive seasons food recognition for calorie detection using SVM and ECOC approaches / Nurul Hafiza Binti Basiruddin, Zalikha Zulkifli and Samsiah Ahmad by Basiruddin, Nurul Hafiza, Zulkifli, Zalikha, Ahmad, Samsiah

“…Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification, which is part of the Support Vector Machine (SVM) algorithm. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

“…The urban growth images obtained are analysed to improve existing classification algorithms. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images by Ibrahim, I., Ibrahim, Z., Khalil, K., Mokji, M.M., Abu Bakar, S.A.R.S., Mokhtar, N., Ahmad, W.K.W.

“…The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects. …”
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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Laser-induced backscattering imaging for classification of seeded and seedless watermelons by Mohd Ali, Maimunah, Hashim, Norhashila, Bejo, Siti Khairunniza, Shamsudin, Rosnah

“…The LDA and kNN-based algorithms also obtained quite high classification accuracies with all the accuracies above 90%. …”
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Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

“…Image representation is one of the major aspects of automatic classification algorithms. …”
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Region-growing based segmentation and bag of features classification for breast ultrasound images by Lee, Lay Khoon

“…In conclusion, region growing segmentation and Bag of features classification able to perform well in ultrasound image.…”
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