Zobrazeno 1 - 10
of 21 028
pro vyhledávání: '"A. Safdar"'
Publikováno v:
Medical Mycology Case Reports, Vol 42, Iss , Pp 100599- (2023)
We present a case of laryngeal cryptococcosis caused by cryptococcosis neoformans var. grubii affecting a patient using excessive inhaled corticosteroids. The patient experienced symptoms for several months prior to specialist review and the visualiz
Externí odkaz:
https://doaj.org/article/4ca7db6e4e1b47169108bbce7df13feb
Publikováno v:
Electrical engineering & Electromechanics, Iss 1, Pp 10-19 (2023)
Introduction. Hybrid electric vehicles are offering the most economically viable choices in today's automotive industry, providing best solutions for a very high fuel economy and low rate of emissions. The rapid progress and development of this indus
Externí odkaz:
https://doaj.org/article/ca1804e23733435e8ee5cf65789ca7db
Autor:
Kim, KiHwan, Chung, Hyunsun, Ahn, Seonghoon, Park, Junhyeok, Jamil, Safdar, Byun, Hongsu, Lee, Myungcheol, Choi, Jinchun, Kim, Youngjae
Log-Structured Merge (LSM) tree-based Key-Value Stores (KVSs) are widely adopted for their high performance in write-intensive environments, but they often face performance degradation due to write stalls during compaction. Prior solutions, such as r
Externí odkaz:
http://arxiv.org/abs/2410.21760
The significant portion of diabetic patients was affected due to major blindness caused by Diabetic retinopathy (DR). For diabetic retinopathy, lesion segmentation, and detection the comprehensive examination is delved into the deep learning techniqu
Externí odkaz:
http://arxiv.org/abs/2409.16721
Autor:
Khan, Asifullah, Sohail, Anabia, Fiaz, Mustansar, Hassan, Mehdi, Afridi, Tariq Habib, Marwat, Sibghat Ullah, Munir, Farzeen, Ali, Safdar, Naseem, Hannan, Zaheer, Muhammad Zaigham, Ali, Kamran, Sultana, Tangina, Tanoli, Ziaurrehman, Akhter, Naeem
Deep supervised learning models require high volume of labeled data to attain sufficiently good results. Although, the practice of gathering and annotating such big data is costly and laborious. Recently, the application of self supervised learning (
Externí odkaz:
http://arxiv.org/abs/2408.17059
Various machine learning (ML)-based in-situ monitoring systems have been developed to detect anomalies and defects in laser additive manufacturing (LAM) processes. While multimodal fusion, which integrates data from visual, audio, and other modalitie
Externí odkaz:
http://arxiv.org/abs/2408.05307
Data-driven research in Additive Manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature to emerge. The knowledge in these works consists of AM and Artificial Intelligence (AI) contexts t
Externí odkaz:
http://arxiv.org/abs/2407.18827
Autor:
Xie, Jiarui, Safdar, Mutahar, Mircea, Andrei, Zhao, Bi Cheng, Lu, Yan, Ko, Hyunwoong, Yang, Zhuo, Zhao, Yaoyao Fiona
Machine learning (ML)-based cyber-physical systems (CPSs) have been extensively developed to improve the print quality of additive manufacturing (AM). However, the reproducibility of these systems, as presented in published research, has not been tho
Externí odkaz:
http://arxiv.org/abs/2407.04031
Autor:
Blankemeier, Louis, Cohen, Joseph Paul, Kumar, Ashwin, Van Veen, Dave, Gardezi, Syed Jamal Safdar, Paschali, Magdalini, Chen, Zhihong, Delbrouck, Jean-Benoit, Reis, Eduardo, Truyts, Cesar, Bluethgen, Christian, Jensen, Malte Engmann Kjeldskov, Ostmeier, Sophie, Varma, Maya, Valanarasu, Jeya Maria Jose, Fang, Zhongnan, Huo, Zepeng, Nabulsi, Zaid, Ardila, Diego, Weng, Wei-Hung, Junior, Edson Amaro, Ahuja, Neera, Fries, Jason, Shah, Nigam H., Johnston, Andrew, Boutin, Robert D., Wentland, Andrew, Langlotz, Curtis P., Hom, Jason, Gatidis, Sergios, Chaudhari, Akshay S.
Over 85 million computed tomography (CT) scans are performed annually in the US, of which approximately one quarter focus on the abdomen. Given the current radiologist shortage, there is a large impetus to use artificial intelligence to alleviate the
Externí odkaz:
http://arxiv.org/abs/2406.06512
Objective: Automated segmentation tools are useful for calculating kidney volumes rapidly and accurately. Furthermore, these tools have the power to facilitate large-scale image-based artificial intelligence projects by generating input labels, such
Externí odkaz:
http://arxiv.org/abs/2405.08282