Search Results - (( code classifications using algorithm ) OR ( image classification methods algorithm ))

Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

“…This paper discusses in detail some of the algorithms used in the pre-processing stages of an offline handwritten character image file. …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…The combination of gist, MTH and SIFT features increased the performance of image identification and showed 49% accuracy. Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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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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Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition by Muhammad Arif, Mohamad, Zalili, Musa, Amelia Ritahani, Ismail

“…With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…Moreover, sparse coding has been commonly used in recent years for the purposes of retrieving and identifying images. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The proposed method will allow for efficient analysis and management of enormous amounts of MRI image data, the earliest practicable early diagnosis, and assistance in the classification of normal, benign, or malignant patient cases. …”
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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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Comparing deep learning CNN method with traditional MRI-based hippocampal segmentation and volumetry for early Alzheimer’s disease diagnosis across diverse populations by Ibrahim, Nur Shahidatul Nabila, Suppiah, Subapriya, Ibrahim, Buhari, Mohad Azmi, Nur Hafizah, Seriramulu, Vengkatha Priya, Mohamad, Mazlyfarina, Hanafi, Marsyita, Mohammad Sallehuddin, Hakimah, Omar Sharif, Nurallysha Najwa, Razali, Rizah Mazzuin, Harrun, Noor Harzana

“…We determined the cut-off thresholds for hippocampal volume to further improve the HippoDeep-driven classification method. CNN-based method outperformed traditional semiautomated method in segmentation accuracy (p < 0.001) with non-significant interpopulation differences. …”
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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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Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

“…The erosion potential categories determined that heavy and severe class covered 35% of the area. Land use/ Land Cover is obtained by satellite image processing that the overall kappa of the classification is 87.4% and the overall accuracy is 89.6%. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali by M. Ali, Musab A.

“…The subsequent step is using the DAUB3 wavelet transform for feature extraction along with the application of an additional step for biometric template security that is the Non-invertible transform (cancelable biometrics method) and finally utilizing the Support Vector Machine (Non-linear Quadratic kernel) for matching/classification. …”
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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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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…This research compares three different methods for extracting features from fruit images to determine which method yields the highest accuracy for fruit classification. …”
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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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The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

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