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

Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

“…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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Segmentation of Lung Region in Computed Tomography (CT) Images by Mohd Bokeri, Husna Adila

“…The proposed method is uses Gaussian smoothing filter followed by thresholding to create binary mask for the lung region. …”
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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning by Siti Zahrah Nur Ain, Silopung

“…This classification is performed using Anaconda and Jupyter Notebok Software that use Python as the programming language. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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A Novel Aggregate Classification Technique Using Moment Invariants and Cascaded Multilayered Perceptron Network by Md Sani, Zamani

“…This article discusses a novel method for automatic classification of aggregate shapes using moment invariants and artificial neural networks. …”
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A Steganalysis Classification Algorithm Based on Distinctive Texture Features by Hammad B.T., Ahmed I.T., Jamil N.

“…As a result, distinguishing between the two symmetric images required the development of methods. Steganalysis is a technique for identifying hidden messages embedded in digital material without having to know the embedding algorithm or the �non-stego� image. …”

Face recognition for varying illumination and different optical zoom using a combination of binary and geometric features by Khalid, Fatimah, Amjeed, Noor, O.K. Wirza, Rahmita Wirza, Madzin, Hizmawati, Azizan, Illiana

“…The proposed method consists of five main stages, starting with eye area detection using the developed Viola-Jones algorithm. …”
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Recent Advances in Classification of Brain Tumor from MR Images – State of the Art Review from 2017 to 2021 by Ghazanfar, Latif, Faisal Yousif, Al Anezi, Dayang Nurfatimah, Awang Iskandar, Abul, Bashar, Jaafar, Alghazo

“…Objective: In this review paper, a detailed summary of the latest techniques used for brain MR image feature extraction and classification is presented. …”
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Novel Feature Extraction and Representation for Currency Classification by Wang, Hui Hui, Wang, Yin Chai, Wee, Bui Lin, Marcus, Chen

“…The methodology consists of five stages, which are image acquisition, image preprocessing, feature extraction, classification, and, lastly, results and analysis. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…The hybrid approach based on image preprocessing and fusion of features is the foundation of the proposed classification method. …”
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Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani by Ghani, Mazuraini

“…This project is all about implementing the back-propagation neural network algorithm in classification of face expression. This project has 3 objectives. …”
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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.

Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation by Mat Ibrahim, Masrullizam, Awang Md Isa, Azmi, Darsono, Abd Majid

“…Based on the segmentation result, the connected components of binary image are used to classify the state of eye whether open or close. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

“…In this study, a multi-scale high-density convolutional neural network (MHCNN) classification method for spatial cognitive ability assessment was proposed, aiming at achieving the binary classification of task-state EEG signals before and after spatial cognitive training. …”
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The Pruning of Combined Neighborhood Differences Texture Descriptor for Multispectral Image Segmentation by Saipullah, Khairul Muzzammil

“…Experimental results, with respect to segmentation and classification accuracy using two LANDSAT multispectral images test suite have been performed. …”
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Effective Deep Features for Image Splicing Detection by Ahmed I.T., Hammad B.T., Jamil N.

Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

“…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

“…There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

“…There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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