Search Results - image classification using

Classification of microcalcification in mammogram images using Enhanced Support Vector Machine (ESVM) / Muhammad Akmal Firdaus... [et al.] by Firdaus, Muhammad Akmal, Shadan, Siti Madinah, Mohd Faudzai, Nur Syahizah

“…Support Vector Machine (SVM) is a supervised machine learning algorithm with the ability to build a classification model from a labeled dataset. SVM has been broadly used in image classification of medical imaging such as mammogram images for breast cancer detection due to its higher classification precision, higher prediction accuracy, better generalization capability and better overall performance. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

“…The first objective of this study is to study the Convolutional Neural Network (CNN) algorithm in the classification of daisy species based on image. Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. …”
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Effect of image compression using fast fourier transformation and discrete wavelet transformation on transfer learning wafer defect image classification by Jessnor Arif, Mat Jizat, Ahmad Fakhri, Ab. Nasir, Anwar P. P., Abdul Majeed, Yuen, Edmund

“…This paper reports on the effect of image compression using Fast Fourier Transformation and Discrete Wavelet Transformation on transfer learning wafer defect image classification. …”
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Brain MRI Tumor Analysis and Classification using Deep Learning by Ghazanfar, Latif

“…In this thesis, an automated multistage technique is proposed for the MR image classification into tumorous and non-tumorous images followed by brain tumor segmentation and classification in order to differentiate the tumors into these four classes using enhanced deep learning models. …”
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Object based image analysis of support vector machine and rule based image classification for building extraction/ Nazatul Asyikin Arham by Arham, Nazatul Asyikin

“…The overall accuracy and kappa coefficient for SVM is 95.11% and 93% respectively and the classification accuracy using rule-based image classification shows 83.49%) and 76%) of overall accuracy and kappa coefficient respectively. …”
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A Novel Method for Fashion Clothing Image Classification Based on Deep Learning by Yoon Shin, Seong, Jo, Gwanghyun, Wang, Guangxing

“…Image recognition and classification is a significant research topic in computational vision and widely used computer technology. …”
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Comparison Of Image Classification Techniques Using Caltech 101 Dataset by Mokhairi, Makhtar, Engku Fadzli Hasan, Syed Abdullah, Nur Shazwani, Kamarudin

“…The use of a set of features to describe 2D shapes in low-level images has been proposed. …”
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Flower image classification modeling using neural network by Siraj, Fadzilah, Mohd Ekhsan, Hawa, Zulkifli, Abdul Nasir

“…Flower image classification is based on the low-level features such as colour and texture to define and describe the image content. …”
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Intelligent methods for automatic classification of medical images / Mohammad Reza Zare by Zare, Mohammad Reza

“…Annotation by binary classification, Annotation by Probabilistic Latent Semantic Analysis (PLSA) and Annotation using top similar images. …”
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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 laser-induced backscattering imaging technique is potentially useful for classification of seeded and seedless watermelons.…”
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Improving Brain MR Image Classification for Tumor Segmentation using Phase Congruency by Ghazanfar, Latif, Dayang Nur Fatimah, Binti Awg Iskandar, Jaafar, Alghazo, Arfan, Jaffar

“…Manual analysis is usually performed by Radiologists on a large set of MR images in order to detect brain tumor. Aims: This research aims to improve automated brain MR image classification and tumor segmentation using phase congruency. …”
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Architecture for biodiversity image retrieval using ontology and Content Based Image Retrieval (CBIR) / Arpah Abu by Abu, Arpah

“…In this study, two models of image retrieval were built; one that does not use image pre-classification, while the other uses image pre-classification. …”
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Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. We then analyzed the classification performance obtained with regard to the image representation techniques used. …”
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Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

“…The usefulness of each of these features will depend on the particular patterns to be highlighted in the image. …”
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Multilevel feature extraction and X-ray image classification by Mueen, A., Baba, M.S., Zainuddin, R.

“…In this study, we propose a new image classification method by using multi-level image features and state-of-the-art machine learning method, Support Vector Machine (SVM). …”
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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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Classification of Diabetic Retinopathy from Fundus Images Using Hybrid Deep Learning Feature Combination and Divide-andConquer Approach by MUHAMMAD MOHSIN, BUTT

“…In this work, a multiclass classification system for DR from fundus images of the eye is proposed. …”
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Ambient-Aware Food Recognition and Management in Context of Smart Fridge by Lau, Christine Yuet Ning

“…Image classification can be done using several classification techniques such as Faster-RCNN, YOLO and SSD. …”
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Unsupervised Classification of Intrusive Igneous Rock Thin Section Images using Edge Detection and Colour Analysis by Silvia, Joseph, Hamimah, Ujir, Irwandi, Hipiny

“…We collected 60 digital images from 20 standard thin sections using a digital camera mounted on a conventional microscope. …”
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Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan by Wan Hasan, Wan Muhammad Akram

“…For this project the samples of different level of ripeness were collected, image processing technique and image classification by using neural network were used. …”
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