Results 11 to 20 of about 1,547,567 (330)

Classifying grains using behaviour-informed machine learning [PDF]

Scientific Reports, 2021
AbstractSorting granular materials such as ores, coffee beans, cereals, gravels and pills is essential for applications in mineral processing, agriculture and waste recycling. Existing sorting methods are based on the detection of contrast in grain properties including size, colour, density and chemical composition.
Sudip Laudari, Benjy Marks, Pierre Rognon   +2 more
openaire   +3 more sources

A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers [PDF]

ACM Transactions on Software Engineering and Methodology, 2022
Software bias is an increasingly important operational concern for software engineers. We present a large-scale, comprehensive empirical study of 17 representative bias mitigation methods for Machine Learning (ML) classifiers, evaluated with 11 ML ...
Zhenpeng Chen, J Zhang, Federica Sarro, M. Harman   +3 more
semanticscholar   +1 more source

A comparative study of gastric histopathology sub-size image classification: From linear regression to visual transformer

Frontiers in Medicine, 2022
IntroductionGastric cancer is the fifth most common cancer in the world. At the same time, it is also the fourth most deadly cancer. Early detection of cancer exists as a guide for the treatment of gastric cancer.
Weiming Hu, Haoyuan Chen, Wanli Liu, Xiaoyan Li, Hongzan Sun, Xinyu Huang, Marcin Grzegorzek, Marcin Grzegorzek, Chen Li   +8 more
doaj   +1 more source

Machine learning classifies cancer [PDF]

Nature, 2018
Brain tumours are often classified by visual assessment of tumour cells, yet such diagnoses can vary depending on the observer. Machine-learning methods to spot molecular patterns could improve cancer diagnosis. Brain tumours are often classified by visual assessment of tumour cells, yet such diagnoses can vary depending on the observer.
Derek, Wong, Stephen, Yip
openaire   +2 more sources

Urban land-use classification using machine learning classifiers: comparative evaluation and post-classification multi-feature fusion approach

European Journal of Remote Sensing, 2023
Accurate spatial-temporal mapping of urban land-use and land-cover (LULC) provides critical information for planning and management of urban environments.
Y. Ouma, Amantle Keitsile, B. Nkwae, P. Odirile, D. Moalafhi, J. Qi   +5 more
semanticscholar   +1 more source

Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms

Cancer Control, 2023
Objective We tested the performance of general machine learning and joint machine learning algorithms in the classification of bone metastasis, in patients with lung adenocarcinoma.
Cheng-Mao Zhou PhD, Ying Wang MD, Qiong Xue MS, Yu Zhu MS   +3 more
doaj   +1 more source

Coast type based accuracy assessment for coastline extraction from satellite image with machine learning classifiers

Egyptian Journal of Remote Sensing and Space Sciences, 2022
Machine learning (ML) classifiers provide convenience and accuracy in coastline extraction compared to traditional methods and image processing techniques.
Osman İsa Çelik, Cem Gazioğlu
doaj   +1 more source

Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers

Italian National Conference on Sensors, 2022
Coronary heart disease is one of the major causes of deaths around the globe. Predicating a heart disease is one of the most challenging tasks in the field of clinical data analysis.
Ch. Anwar ul Hassan, Jawaid Iqbal, Rizwana Irfan, Saddam Hussain, Abeer D. Algarni, Syed Nisar Hussain Bukhari, Nazik Alturki, Syed Sajid Ullah   +7 more
semanticscholar   +1 more source

Machine learning for identification of dental implant systems based on shape – A descriptive study

The Journal of Indian Prosthodontic Society, 2021
Aim: To evaluate the efficacy of machine learning in identification of dental implant systems from panoramic radiographs based on the shape. Settings and Design: In vitro–Descriptive study Materials and Methods: A Dataset of digital panoramic radiographs
Veena Basappa Benakatti, Ramesh P Nayakar, Mallikarjun Anandhalli   +2 more
doaj   +1 more source

Semantic segmentation model for land cover classification from satellite images in Gambella National Park, Ethiopia

SN Applied Sciences, 2023
Article highlights Built semantic segmentation models using machine learning classifiers (SVM and RF), and deep learning using LinkNet with ResNet34 as encoder techniques. Presents the semantic segmentation for land cover classification.
Mulugeta Yikuno Lilay, Gizatie Desalegn Taye   +1 more
doaj   +1 more source