Zobrazeno 1 - 10
of 1 924
pro vyhledávání: '"Mackin, P"'
Autor:
Vijayaraghavan, Prashanth, Shi, Luyao, Ambrogio, Stefano, Mackin, Charles, Nitsure, Apoorva, Beymer, David, Degan, Ehsan
With the unprecedented advancements in Large Language Models (LLMs), their application domains have expanded to include code generation tasks across various programming languages. While significant progress has been made in enhancing LLMs for popular
Externí odkaz:
http://arxiv.org/abs/2406.04379
Autor:
Peng, Tianhao, Feng, Chen, Danier, Duolikun, Zhang, Fan, Vallade, Benoit, Mackin, Alex, Bull, David
With recent advances in deep learning, numerous algorithms have been developed to enhance video quality, reduce visual artifacts, and improve perceptual quality. However, little research has been reported on the quality assessment of enhanced content
Externí odkaz:
http://arxiv.org/abs/2405.08621
Autor:
Lowe, Scott C., Misiuk, Benjamin, Xu, Isaac, Abdulazizov, Shakhboz, Baroi, Amit R., Bastos, Alex C., Best, Merlin, Ferrini, Vicki, Friedman, Ariell, Hart, Deborah, Hoegh-Guldberg, Ove, Ierodiaconou, Daniel, Mackin-McLaughlin, Julia, Markey, Kathryn, Menandro, Pedro S., Monk, Jacquomo, Nemani, Shreya, O'Brien, John, Oh, Elizabeth, Reshitnyk, Luba Y., Robert, Katleen, Roelfsema, Chris M., Sameoto, Jessica A., Schimel, Alexandre C. G., Thomson, Jordan A., Wilson, Brittany R., Wong, Melisa C., Brown, Craig J., Trappenberg, Thomas
Advances in underwater imaging enable the collection of extensive seafloor image datasets that are necessary for monitoring important benthic ecosystems. The ability to collect seafloor imagery has outpaced our capacity to analyze it, hindering exped
Externí odkaz:
http://arxiv.org/abs/2405.05241
Professionally generated content (PGC) streamed online can contain visual artefacts that degrade the quality of user experience. These artefacts arise from different stages of the streaming pipeline, including acquisition, post-production, compressio
Externí odkaz:
http://arxiv.org/abs/2312.08859
Autor:
Feng, Chen, Danier, Duolikun, Wang, Haoran, Zhang, Fan, Vallade, Benoit, Mackin, Alex, Bull, David
Deep learning-based video quality assessment (deep VQA) has demonstrated significant potential in surpassing conventional metrics, with promising improvements in terms of correlation with human perception. However, the practical deployment of such de
Externí odkaz:
http://arxiv.org/abs/2312.08864
Autor:
Georgina B. F. Hall, Rachael Birkbeck, Benjamin M. Brainard, Fernanda Camacho, Elizabeth B. Davidow, Dana N. LeVine, Andrew Mackin, Taylor Moss, Katherine J. Nash, Giacomo Stanzani, Daria Starybrat, David Q. Stoye, Carolyn Tai, John Thomason, Julie M. Walker, K. Jane Wardrop, Helen Wilson, Virginie A. Wurlod, Karen Humm
Publikováno v:
Journal of Veterinary Internal Medicine, Vol 38, Iss 5, Pp 2495-2506 (2024)
Abstract Background Reported incidence of blood transfusion reactions (TR) varies greatly. Objective To prospectively evaluate the incidence of acute TRs in dogs receiving allogenic blood products, using consensus definitions, and to assess factors a
Externí odkaz:
https://doaj.org/article/fa536a4ec50a47b1bbf67a6e84e846b7
Autor:
Gallo, Manuel Le, Lammie, Corey, Buechel, Julian, Carta, Fabio, Fagbohungbe, Omobayode, Mackin, Charles, Tsai, Hsinyu, Narayanan, Vijay, Sebastian, Abu, Maghraoui, Kaoutar El, Rasch, Malte J.
Publikováno v:
APL Machine Learning (2023) 1 (4): 041102
Analog In-Memory Computing (AIMC) is a promising approach to reduce the latency and energy consumption of Deep Neural Network (DNN) inference and training. However, the noisy and non-linear device characteristics, and the non-ideal peripheral circuit
Externí odkaz:
http://arxiv.org/abs/2307.09357
Autor:
Dana N. LeVine, Linda Kidd, Oliver A. Garden, Marjory B. Brooks, Robert Goggs, Barbara Kohn, Andrew J. Mackin, Erin R. B. Eldermire, Yu‐Mei Chang, Julie Allen, Peter W. Christopherson, Barbara Glanemann, Haruhiko Maruyama, Maria C. Naskou, Lise N. Nielsen, Sarah Shropshire, Austin K. Viall, Adam J. Birkenheuer, Marnin A. Forman, Andrew S. Hanzlicek, Kathrin F. Langner, Erin Lashnits, Katharine F. Lunn, Kelly M. Makielski, Xavier Roura, Eva Spada
Publikováno v:
Journal of Veterinary Internal Medicine, Vol 38, Iss 4, Pp 1958-1981 (2024)
Abstract Immune thrombocytopenia (ITP) is the most common acquired primary hemostatic disorder in dogs. Immune thrombocytopenia less commonly affects cats but is an important cause of mortality and treatment‐associated morbidity in both species. Im
Externí odkaz:
https://doaj.org/article/2034370a28c34958bb3b2126708ad6f0
Autor:
Dana N. LeVine, Robert Goggs, Barbara Kohn, Andrew J. Mackin, Linda Kidd, Oliver A. Garden, Marjory B. Brooks, Erin R. B. Eldermire, Anthony Abrams‐Ogg, Elizabeth H. Appleman, Todd M. Archer, Domenico Bianco, Shauna L. Blois, Benjamin M. Brainard, Mary Beth Callan, Claire L. Fellman, Jillian M. Haines, Anne S. Hale, Alice A. Huang, John M. Lucy, Shana K. O'Marra, Elizabeth A. Rozanski, John M. Thomason, Jenny E. Walton, Helen E. Wilson
Publikováno v:
Journal of Veterinary Internal Medicine, Vol 38, Iss 4, Pp 1982-2007 (2024)
Abstract Management of immune thrombocytopenia (ITP) in dogs and cats is evolving, but there are no evidence‐based guidelines to assist clinicians with treatment decisions. Likewise, the overall goals for treatment of ITP have not been established.
Externí odkaz:
https://doaj.org/article/fec500a7843946a5a835daee9da14c8d
Autor:
Rasch, Malte J., Mackin, Charles, Gallo, Manuel Le, Chen, An, Fasoli, Andrea, Odermatt, Frederic, Li, Ning, Nandakumar, S. R., Narayanan, Pritish, Tsai, Hsinyu, Burr, Geoffrey W., Sebastian, Abu, Narayanan, Vijay
Analog in-memory computing (AIMC) -- a promising approach for energy-efficient acceleration of deep learning workloads -- computes matrix-vector multiplications (MVMs) but only approximately, due to nonidealities that often are non-deterministic or n
Externí odkaz:
http://arxiv.org/abs/2302.08469