Zobrazeno 1 - 10
of 27 403
pro vyhledávání: '"Parida A"'
Publikováno v:
Aksioma: Jurnal Program Studi Pendidikan Matematika, Vol 12, Iss 2, Pp 2586-2598 (2023)
This study aims to produce chatbot scaffolding media with a PjBL model in e-lematika to improve student learning outcomes in class VIII Cartesian cooordinat material that is appropriate for use in the learning process. This research is a development
Externí odkaz:
https://doaj.org/article/a968c7bda33a4de7a2ac8b6d3f925c9e
Sign System sebagai Media Komunikasi Visual Pengrajin Sasirangan di Kampung Sasirangan Kertak Hanyar
Publikováno v:
E-Dimas, Vol 14, Iss 2, Pp 393-398 (2023)
Sentra UMKM kerajinan sasirangan di Kabupaten Banjar satu di antaranya terletak di Kampung Sasirangan Kecamatan Kertak Hanyar. Permasalahan yang perlu diselesaikan adalah belum tersedianya sign system di lokasi UMKM. Tujuan dirancangnya sign system y
Externí odkaz:
https://doaj.org/article/f35b51052785476bb1d848709f53e15c
Autor:
Nevy Farista Aristin, Karunia Puji Hastuti, Indra Setiawan, Sidharta Adyatma, Parida Angriani
Publikováno v:
Jambura Geo Education Journal, Vol 4, Iss 1, Pp 77-83 (2023)
The learning process communication deficiency is caused by the tendency to use media that still needs to be more effective. Learning media, such as booklets, supports the achievement of learning objectives. Experimental research with a nonequivalent
Externí odkaz:
https://doaj.org/article/064fb207c2114e6d93e40b5932ad5805
Autor:
Patra, Subhajit, Panda, Sonali, Parida, Bikram Keshari, Arya, Mahima, Jacobs, Kurt, Bondar, Denys I., Sen, Abhijit
Physics-informed neural networks have proven to be a powerful tool for solving differential equations, leveraging the principles of physics to inform the learning process. However, traditional deep neural networks often face challenges in achieving h
Externí odkaz:
http://arxiv.org/abs/2407.18373
Event-by-event fluctuations in the initial stages of ultrarelativistic nucleus-nucleus collisions depend little on rapidity. The hydrodynamic expansion which occurs in later stages then gives rise to correlations among outgoing particles which depend
Externí odkaz:
http://arxiv.org/abs/2407.17313
Autor:
Parida, Abhijeet, Alomar, Antonia, Jiang, Zhifan, Roshanitabrizi, Pooneh, Tapp, Austin, Ledesma-Carbayo, Maria, Xu, Ziyue, Anwar, Syed Muhammed, Linguraru, Marius George, Roth, Holger R.
Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory hurdles associated with site-specific fine-tuning. For histopathology, stain normalization techniques
Externí odkaz:
http://arxiv.org/abs/2407.13632
Autor:
Shi, Shanghao, Haque, Md Shahedul, Parida, Abhijeet, Linguraru, Marius George, Hou, Y. Thomas, Anwar, Syed Muhammad, Lou, Wenjing
Federated learning (FL) allows a set of clients to collaboratively train a machine-learning model without exposing local training samples. In this context, it is considered to be privacy-preserving and hence has been adopted by medical centers to tra
Externí odkaz:
http://arxiv.org/abs/2407.09972
Large language models (LLMs) demonstrated transformative capabilities in many applications that require automatically generating responses based on human instruction. However, the major challenge for building LLMs, particularly in Indic languages, is
Externí odkaz:
http://arxiv.org/abs/2407.09855
Autor:
Shaukat, Furqan, Anwar, Syed Muhammad, Parida, Abhijeet, Lam, Van Khanh, Linguraru, Marius George, Shah, Mubarak
Lung cancer has been one of the major threats to human life for decades. Computer-aided diagnosis can help with early lung nodul detection and facilitate subsequent nodule characterization. Large Visual Language models (VLMs) have been found effectiv
Externí odkaz:
http://arxiv.org/abs/2407.02625
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions
Autor:
Nisar, Hareem, Anwar, Syed Muhammad, Jiang, Zhifan, Parida, Abhijeet, Sanchez-Jacob, Ramon, Nath, Vishwesh, Roth, Holger R., Linguraru, Marius George
Large vision language models (VLMs) have progressed incredibly from research to applicability for general-purpose use cases. LLaVA-Med, a pioneering large language and vision assistant for biomedicine, can perform multi-modal biomedical image and dat
Externí odkaz:
http://arxiv.org/abs/2407.02604