Results 1 to 10 of about 6,515,077 (343)

Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks [PDF]

Physical and Engineering Sciences in Medicine, 2020
In this study, a dataset of X-ray images from patients with common bacterial pneumonia, confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection of the Coronavirus disease.
Ioannis D Apostolopoulos
exaly   +2 more sources

Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study

Gut, 2019
Objective The effect of colonoscopy on colorectal cancer mortality is limited by several factors, among them a certain miss rate, leading to limited adenoma detection rates (ADRs).
Pu Wang, Tyler M Berzin, Jeremy Romek Glissen Brown   +2 more
exaly   +2 more sources

Automatic Detection and Proximity Quantification of Inferior Alveolar Nerve and Mandibular Third Molar on CBCT: A Systematic Review

Journal of Pharmacy and Bioallied Sciences
The present systematic review aimed to investigate AI-based automated identification and proximity quantification of the inferior alveolar nerve (IAN) and the mandibular third molar (M3) on CBCT images. Precise localization of the IAN is important in the
Abdullah R. F. Alanazi, Saud A. T. Alshammari, Salman A. S. Aljudaya, Dari A. S. Alshammri, Faisal M. S. Alazmi, Namdeo Prabhu   +5 more
doaj   +2 more sources

Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networks [PDF]

Pattern Analysis and Applications, 2020
The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread rapidly among people living in other countries and is approaching approximately 101,917,147 cases worldwide according to the statistics of World Health Organization.
A. Narin, Ceren Kaya, Ziynet Pamuk
semanticscholar   +1 more source

COMPARATIVE ANALYSIS OF GOST R AND IMO MSC/CIRC. REQUIREMENTS DETERMINING THE QUALITY OF FOAMING AGENTS USED FOR FIRE EXTINGUISHING BY FOAMS [PDF]

Актуальные вопросы пожарной безопасности, 2020
The article provides the analysis of the GOST R and IMO MSC/Circ. requirements determining the quality of foaming agents used for fire extinguishing by foams.
Sergey N. Kopylov, Dmitry S. Shentyapin, Evgeny V. Baranov, Vladimir V. Grishin, Evgeny E. Arkhipov   +4 more
doaj   +1 more source

A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique

IEEE Access, 2021
Breast cancer (BC) is one of the primary causes of cancer death among women. Early detection of BC allows patients to receive appropriate treatment, thus increasing the possibility of survival.
Abeer Saber, Mohamed Sakr, O. M. Abo-Seida, Arabi Keshk, Huiling Chen   +4 more
semanticscholar   +1 more source

AI-Based Automatic Detection and Classification of Diabetic Retinopathy Using U-Net and Deep Learning

Symmetry, 2022
Artificial intelligence is widely applied to automate Diabetic retinopathy diagnosis. Diabetes-related retinal vascular disease is one of the world’s most common leading causes of blindness and vision impairment. Therefore, automated DR detection systems
A. Bilal, Liucun Zhu, Anan Deng, Huihui Lu, Ning Wu   +4 more
semanticscholar   +1 more source

Automatic detection of COVID-19 infection using chest X-ray images through transfer learning

IEEE/CAA Journal of Automatica Sinica, 2021
The new coronavirus ( COVID-19 ) , declared by the World Health Organization as a pandemic, has infected more than 1 million people and killed more than 50 thousand.
E. F. Ohata, G. M. Bezerra, J. V. S. D. Chagas, A. V. L. Neto, A. Albuquerque, V. Albuquerque, P. Filho   +6 more
semanticscholar   +1 more source

Automatic Sarcasm Detection [PDF]

ACM Computing Surveys, 2017
Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text. Beginning with an approach that used speech-based features, automatic sarcasm detection has witnessed great interest from the sentiment analysis community.
Joshi A., Bhattacharyya P., Carman M. J.
openaire   +3 more sources

Feature-Level Attentive Neural Model for Session-Based Recommendation

IEEE Access, 2020
The main goal of session-based recommendation is to predict a user's next click based on historical anonymous session data. One important aspect is capturing the interest drift that occurs in a user's click sequences. Recent studies have mainly exploited
Qing Yang, Peicheng Luo, Xinghe Cheng, Ning Li, Jingwei Zhang   +4 more
doaj   +1 more source