Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Md Junayed Hasan"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract This work addresses a critical issue: the deterioration of concrete structures due to fine-grained cracks, which compromises their strength and longevity. To tackle this problem, experts have turned to computer vision (CV) based automated st
Externí odkaz:
https://doaj.org/article/6aed467d02c441e3b6389b7eca784c45
Autor:
Rezaul Haque, Abdullah Al Sakib, Md Forhad Hossain, Fahadul Islam, Ferdaus Ibne Aziz, Md Redwan Ahmed, Somasundar Kannan, Ali Rohan, Md Junayed Hasan
Publikováno v:
BioMedInformatics, Vol 4, Iss 2, Pp 966-991 (2024)
Disease recognition has been revolutionized by autonomous systems in the rapidly developing field of medical technology. A crucial aspect of diagnosis involves the visual assessment and enumeration of white blood cells in microscopic peripheral blood
Externí odkaz:
https://doaj.org/article/36ebf634f8214dedbfb5b2dcb283d55d
Autor:
Syed Ahmmed, Prajoy Podder, M. Rubaiyat Hossain Mondal, S M Atikur Rahman, Somasundar Kannan, Md Junayed Hasan, Ali Rohan, Alexander E. Prosvirin
Publikováno v:
BioMedInformatics, Vol 3, Iss 4, Pp 1124-1144 (2023)
This study focuses on leveraging data-driven techniques to diagnose brain tumors through magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we introduce and fine-tune two robust frameworks, ResNet 50 and Inception V3,
Externí odkaz:
https://doaj.org/article/8b386f2859d748498b71d3e1d7b9e985
Publikováno v:
Sensors, Vol 23, Iss 10, p 4875 (2023)
Gait recognition, also known as walking pattern recognition, has expressed deep interest in the computer vision and biometrics community due to its potential to identify individuals from a distance. It has attracted increasing attention due to its po
Externí odkaz:
https://doaj.org/article/d9b91924003c48ebb0c65b1a1d4bb642
Autor:
Prajoy Podder, Fatema Binte Alam, M. Rubaiyat Hossain Mondal, Md Junayed Hasan, Ali Rohan, Subrato Bharati
Publikováno v:
Computers, Vol 12, Iss 5, p 95 (2023)
Due to its high transmissibility, the COVID-19 pandemic has placed an unprecedented burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a valuable and cost-effective tool for detecting and diagnosing COVID-19 patients. I
Externí odkaz:
https://doaj.org/article/5848c889da9d4aefb7148926b059dcae
Publikováno v:
Computers, Vol 12, Iss 4, p 87 (2023)
With the proliferation of the internet, social networking sites have become a primary source of user-generated content, including vast amounts of information about medications, diagnoses, treatments, and disorders. Comments on previously used medicin
Externí odkaz:
https://doaj.org/article/8bd6d487826c41ef848fe04608fa921f
Publikováno v:
IEEE Access, Vol 9, Pp 58052-58066 (2021)
Centrifugal pumps are the most vital part of any process industry. A fault in centrifugal pump can affect imperative industrial processes. To ensure reliable operation of the centrifugal pump, this paper proposes a novel automated health state diagno
Externí odkaz:
https://doaj.org/article/58a16d81c43c4a2ebcf518b85d298fe4
Publikováno v:
IEEE Access, Vol 9, Pp 150128-150141 (2021)
In this paper, we propose a three-stage lightweight framework for centrifugal pump fault diagnosis. First, the centrifugal pump vibration signatures are fast transformed using a Walsh transform, and Walsh spectra are obtained. To overcome the hefty n
Externí odkaz:
https://doaj.org/article/f4d26df1f24045508ee8c20f2cdd9a62
Autor:
Prajoy Podder, Sanchita Rani Das, M. Rubaiyat Hossain Mondal, Subrato Bharati, Azra Maliha, Md Junayed Hasan, Farzin Piltan
Publikováno v:
Sensors, Vol 23, Iss 1, p 480 (2023)
This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The pro
Externí odkaz:
https://doaj.org/article/3626e1c9987d46a2bfce02a5a40f3404
Publikováno v:
Sensors, Vol 21, Iss 24, p 8247 (2021)
Pipeline leakage remains a challenge in various industries. Acoustic emission (AE) technology has recently shown great potential for leak diagnosis. Many AE features, such as root mean square (RMS), peak value, standard deviation, mean value, and ent
Externí odkaz:
https://doaj.org/article/247a9aaf76bf4939a48f81993474b881