An unsupervised-learning-based approach for automated defect inspection on textured surfaces

S Mei, H Yang, Z Yin - IEEE transactions on instrumentation …, 2018 - ieeexplore.ieee.org
Automated defect inspection has long been a challenging task especially in industrial
applications, where collecting and labeling large amounts of defective samples are usually …

Brain asymmetry detection and machine learning classification for diagnosis of early dementia

NJ Herzog, GD Magoulas - Sensors, 2021 - mdpi.com
Early identification of degenerative processes in the human brain is considered essential for
providing proper care and treatment. This may involve detecting structural and functional …

An autonomous technique for weld defects detection and classification using multi-class support vector machine in X-radiography image

M Malarvel, H Singh - Optik, 2021 - Elsevier
Non-destructive tests are a major evaluation process in the metal, oil, and gas industries. In
these industries, weld defect inspection is one of the important parts of testing. Manual …

Automated oral squamous cell carcinoma identification using shape, texture and color features of whole image strips

TY Rahman, LB Mahanta, AK Das, JD Sarma - Tissue and Cell, 2020 - Elsevier
Despite profound knowledge of the incidence of oral cancers and a large body of research
beyond it, it continues to beat diagnosis and treatment management. Post physical …

Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques

TY Rahman, LB Mahanta, H Choudhury… - Cancer …, 2020 - Wiley Online Library
Background Oral squamous cell carcinoma (OSCC) is the most prevalent form of oral
cancer. Very few researches have been carried out for the automatic diagnosis of OSCC …

Textural pattern classification for oral squamous cell carcinoma

TY Rahman, LB Mahanta, C Chakraborty… - Journal of …, 2018 - Wiley Online Library
Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains
to be widely researched. Studies on computer‐aided analysis of pathological slides of oral …

Automatic classification of flying bird species using computer vision techniques

J Atanbori, W Duan, J Murray, K Appiah… - Pattern Recognition …, 2016 - Elsevier
Bird populations are identified as important biodiversity indicators, so collecting reliable
population data is important to ecologists and scientists. However, existing manual …

Comparison of Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and Stochastic Gradient Descent (SGD) for Classifying Corn Leaf Disease based on …

F Solihin, M Syarief, EMS Rochman… - Elinvo (Electronics …, 2023 - journal.uny.ac.id
Image classification involves categorizing an image's pixels into specific classes based on
their unique characteristics. It has diverse applications in everyday life. One such application …

A hybrid model of PSO algorithm and artificial neural network for automatic follicle classification

OR Isah, AD Usman, AM Tekanyi - 2017 - repository.futminna.edu.ng
Polycystic Ovarian Syndrome (PCOS) is one of the leading causes of infertility in the world,
but is a preventable disease when detected early. Detection of follicles in ultrasound images …

Dynamic weights equations for converting grayscale image to RGB image

SAH Alrubaie, AH Hameed - … of University of Babylon for Pure …, 2018 - journalofbabylon.com
The method of converting color images from the RGB color system to grayscale images is a
simple operation by using the fixed weights method of conversion, but using the same …