Search Results - (( tissues classification based algorithm ) OR ( java application stemming algorithm ))

Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter by Tengku Azis, Tengku Mohd Syamim

“…One of the main processing technique in CAD is texture classification and analysis. In this research, a Gabor-based emphysema classification algorithm is proposed. …”
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

“…The selected subset of genes is then be used to train the classifiers for constructing rules for future tissue classification problem. Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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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.

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Detection and Classification of Granulation Tissue in Chronic Ulcers by Ahmad Fadzil, Mohd Hani

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A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim by Ibrahim, Shafaf

“…It is designed to incorporate with the CAPSOCA algorithm which intended to strengthen the classification outcomes. …”
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Development of sorting system for oil palm in vitro shoots using machine vision approach by Al-Ruhaimi, Hamdan Yahya Ahmed

“…Based on SOTA and classification task decision, a sorting algorithm that can acquire, recognize, and eject a shoot has been improved and tested in an offline mode. …”
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Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images by Gandhamal, A., Talbar, S., Gajre, S., Hani, A.F.M., Kumar, D.

“…Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. …”
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Texture Classification of lung computed tomography (CT) using local binary patterns (LBP) by MOHD YUSRI, MOHAMAD AFIF SYAUQI

“…In this work, we proposed an LBP-based lung classification algorithm. The local binary pattern (LBP) is one of the feature extraction technique that can be used in classify the image. …”
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Breast cancer classification using mammography image and K-Nearest Neighbour / Najihah Ahmad Latif by Ahmad Latif, Najihah

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Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique by Jais, Fatin Nabihah, Che Azemin, Mohd Zulfaezal, Hilmi, Mohd Radzi, Mohd Tamrin, Mohd Izzuddin, Mohd. Kamal, Khairidzan

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Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Fatimah, Dzaharudin, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

“…Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. …”
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Breast cancer histological images nuclei segmentation and optimized classification with deep learning by Abbasi, Muhammad Inam, Khan, Fawad Salam, Khurram, Muhammad, Mohd, Mohd Norzali, Khan, Muhammad Danial

“…The extracted features map using the feature pyramid network has been modified using segmenting objects by locations (SOLO) convolution with grasshopper optimization for multiclass classification. A breast cancer multi-classification technique based on a suggested deep learning algorithm was examined to achieve the accuracy of 99.2% using a huge database of ICIAR 2018, demonstrating the method’s efficacy in offering an important weapon for breast cancer multi-classification in a medical setting. …”
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Automated classification radiograph of Periodontal bone loss using deep learning by Al Husaini, Mohammed Abdulla Salim, Habaebi, Mohamed Hadi, Yadav, Seema

“…This study highlights the potential of deep learning-based OPG classification systems to assist dental professionals in faster and more accurate detection of periodontal diseases.…”
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Automated Segmentation And Classification Technique For Brain Stroke by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim, Mohd Noor, Niza Suzaini, Mohd Ali, Nursabillilah

“…This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). …”
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Evaluation of heuristic-based MicroRNA marker selection techniques for classification of cancer by Razak, Eliza, Yusof, Faridah, Ahmad Raus, Raha

“…In this paper, we employed three marker selection algorithms to select relevant miRNAs that are directly responsible for cancer classification. …”
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Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

“…The results of analyzing different predictive multiclass classification models with taxi trip tolls show that it is possible to use a machine learning-based model when we like to avoid road tolls depending on historical data on taxi trip tolls. …”
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EMG signal classification for human computer interaction: a review by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…This review paper is to discuss the various methodologies and algorithms used for EMG signal classification for the purpose of interpreting the EMG signal into computer command.…”
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Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS by Al-Shoukry S., Jawad B.J.M., Musa Z., Sabry A.H.

“…The results of analyzing different predictive multiclass classification models with taxi trip tolls show that it is possible to use a machine learning-based model when we like to avoid road tolls depending on historical data on taxi trip tolls. …”