Zobrazeno 1 - 10
of 483
pro vyhledávání: '"Asoke K. Nandi"'
Autor:
Hosameldin O. A. Ahmed, Asoke K. Nandi
Publikováno v:
IEEE Access, Vol 12, Pp 133703-133725 (2024)
As breast cancer is a leading cause of death for women globally, there is a critical need for better diagnostic tools. To address this challenge, we propose MoEffNet, a cutting-edge framework that offers high-performance breast cancer diagnosis. MoEf
Externí odkaz:
https://doaj.org/article/158cb0936c254901a8d84ea8ffcd0fab
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 8, Iss 4, Pp 1178-1190 (2023)
Abstract Aerial scene recognition (ASR) has attracted great attention due to its increasingly essential applications. Most of the ASR methods adopt the multi‐scale architecture because both global and local features play great roles in ASR. However
Externí odkaz:
https://doaj.org/article/0d57e2d7227545578a6375d517a39814
Publikováno v:
Applied Sciences, Vol 14, Iss 6, p 2253 (2024)
Bearings are one of the critical components of rotating machinery, and their failure can cause catastrophic consequences. In this regard, previous studies have proposed a variety of intelligent diagnosis methods. Most existing bearing fault diagnosis
Externí odkaz:
https://doaj.org/article/05f18dcc4ba5410b8719ddc34e1212f6
Autor:
Asoke K. Nandi
Publikováno v:
IEEE Access, Vol 11, Pp 3899-3913 (2023)
It is extremely common in engineering to design algorithms to perform various tasks. In data-driven decision making in any field one needs to ascertain the quality of an algorithm. Therefore, a robust assessment of algorithms is essential in deciding
Externí odkaz:
https://doaj.org/article/5e810c4139064d54bce4ddac2b462bbe
Publikováno v:
IET Image Processing, Vol 16, Iss 5, Pp 1243-1267 (2022)
Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation using deep l
Externí odkaz:
https://doaj.org/article/b6197d5d75c143e38c025cf2871d6c00
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 7308-7322 (2022)
Change detection is an important task of identifying changed information by comparing bitemporal images over the same geographical area. Currently, many existing methods based on U-Net and attention mechanism have greatly promoted the development of
Externí odkaz:
https://doaj.org/article/18c0a714e8df4174a057dbf381af9de8
Publikováno v:
IET Image Processing, Vol 15, Iss 14, Pp 3522-3533 (2021)
Abstract Although deep learning has been widely used for dense crowd counting, it still faces two challenges. Firstly, the popular network models are sensitive to scale variance of human head, human occlusions, and complex background due to repeated
Externí odkaz:
https://doaj.org/article/8b12265dc6084314af4d3093b0140ab0
Autor:
Hosameldin O. A. Ahmed, Asoke K. Nandi
Publikováno v:
Machines, Vol 11, Iss 7, p 746 (2023)
Fault diagnosis of bearings in rotating machinery is a critical task. Vibration signals are a valuable source of information, but they can be complex and noisy. A transformer model can capture distant relationships, which makes it a promising solutio
Externí odkaz:
https://doaj.org/article/491063269bfa42628e7d970c2b64081e
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 1796-1809 (2021)
Popular unsupervised change detection algorithms suffer from two problems: first, the difference image generated by bitemporal images usually includes a large number of falsely changed regions due to noise corruption and illumination change; second,
Externí odkaz:
https://doaj.org/article/e31ed5b0750d40c2a394d04440d39ae4
Publikováno v:
Frontiers in Signal Processing, Vol 2 (2022)
Edge detection technology aims to identify and extract the boundary information of image pixel mutation, which is a research hotspot in the field of computer vision. This technology has been widely used in image segmentation, target detection, and ot
Externí odkaz:
https://doaj.org/article/d4c5eecf320a4d8792b9bb4d914047dc