Zobrazeno 1 - 10
of 133 604
pro vyhledávání: '"Ullah A."'
Autor:
Ullah A., Khan K., Bibi N., Ahmad S., Khan A., Ali M., Ali H., Khan M. F., Ghayyur S., Yasmin S., Ul Haq A.
Publikováno v:
Helminthologia, Vol 59, Iss 4, Pp 398-403 (2022)
More than 24,000 species of helminth parasitize wild birds worldwide, and this number is expanding as interest in wildlife parasitology increases. The objective of the current study was to update the baseline of helminthological surveys conducted on
Externí odkaz:
https://doaj.org/article/7fd78733c51240c090f9361524117e17
Autor:
Khan, Muhammad Saif Ullah, Khan, Muhammad Ahmed Ullah, Afzal, Muhammad Zeshan, Stricker, Didier
This paper reformulates cross-dataset human pose estimation as a continual learning task, aiming to integrate new keypoints and pose variations into existing models without losing accuracy on previously learned datasets. We benchmark this formulation
Externí odkaz:
http://arxiv.org/abs/2409.20469
Autor:
Bhimji, Wahid, Calafiura, Paolo, Chakkappai, Ragansu, Chou, Yuan-Tang, Diefenbacher, Sascha, Dudley, Jordan, Farrell, Steven, Ghosh, Aishik, Guyon, Isabelle, Harris, Chris, Hsu, Shih-Chieh, Khoda, Elham E, Lyscar, Rémy, Michon, Alexandre, Nachman, Benjamin, Nugent, Peter, Reymond, Mathis, Rousseau, David, Sluijter, Benjamin, Thorne, Benjamin, Ullah, Ihsan, Zhang, Yulei
The FAIR Universe -- HiggsML Uncertainty Challenge focuses on measuring the physics properties of elementary particles with imperfect simulators due to differences in modelling systematic errors. Additionally, the challenge is leveraging a large-comp
Externí odkaz:
http://arxiv.org/abs/2410.02867
Autor:
Sarode, Shalini, Khan, Muhammad Saif Ullah, Shehzadi, Tahira, Stricker, Didier, Afzal, Muhammad Zeshan
We propose ClassroomKD, a novel multi-mentor knowledge distillation framework inspired by classroom environments to enhance knowledge transfer between student and multiple mentors. Unlike traditional methods that rely on fixed mentor-student relation
Externí odkaz:
http://arxiv.org/abs/2409.20237
Autor:
Duong, Ngoc My Hanh, Berhane, Amanuel M., Mitchell, Dave, Ullah, Rifat, Zhang, Ting, Zhu, He, Du, Jia, Lam, Simon K. H., Mitchell, Emma E., Bendavid, Avi
In this letter, we demonstrate for the first time the creation of Josephson-like superconducting nanojunctions using a thermal scanning probe to directly inscribe weak links into microstrips of YBa2Cu3O7-x (YBCO). Our method effectively reduces the c
Externí odkaz:
http://arxiv.org/abs/2410.00372
Publikováno v:
European Physical Journal A 60:75 (2024)
The beta-decay log ft values for 210 215Pb 210 215Bi and 210 215Bi 210 215Po transitions in the north east region of 208Pb nuclei are estimated using the proton neutron quasiparticle random phase approximation model. The pn-QRPA equations were solved
Externí odkaz:
http://arxiv.org/abs/2409.12565
Autor:
Khan, Wali Ullah, Lagunas, Eva, Mahmood, Asad, Asif, Muhammad, Ahmed, Manzoor, Chatzinotas, Symeon
The reconfigurable intelligent surface (RIS) technology shows great potential in sixth-generation (6G) terrestrial and non-terrestrial networks (NTNs) since it can effectively change wireless settings to improve connectivity. Extensive research has b
Externí odkaz:
http://arxiv.org/abs/2409.06073
Publikováno v:
Ecological Informatics, Volume 83, 2024, 102805, ISSN 1574-9541, (https://www.sciencedirect.com/science/article/pii/S1574954124003479)
Camera trap imagery has become an invaluable asset in contemporary wildlife surveillance, enabling researchers to observe and investigate the behaviors of wild animals. While existing methods rely solely on image data for classification, this may not
Externí odkaz:
http://arxiv.org/abs/2409.04825
In Generalized Zero-Shot Learning (GZSL), we aim to recognize both seen and unseen categories using a model trained only on seen categories. In computer vision, this translates into a classification problem, where knowledge from seen categories is tr
Externí odkaz:
http://arxiv.org/abs/2409.00511
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