Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Catherine F. Higham"'
Autor:
Catherine F. Higham, Adrian Bedford
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract We demonstrate the feasibility of framing a classically learned deep neural network as an energy based model that can be processed on a one-step quantum annealer in order to exploit fast sampling times. We propose approaches to overcome two
Externí odkaz:
https://doaj.org/article/25077469cba94e5497d560ed2c25f4f0
Publikováno v:
Frontiers in Artificial Intelligence, Vol 3 (2020)
Learning a second language (L2) usually progresses faster if a learner's L2 is similar to their first language (L1). Yet global similarity between languages is difficult to quantify, obscuring its precise effect on learnability. Further, the combinat
Externí odkaz:
https://doaj.org/article/2ccee181fbf64839afa95d341676da06
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Autor:
Catherine F. Higham, Desmond J. Higham
Publikováno v:
Higham, C F & Higham, D J 2019, ' Deep learning: an introduction for applied mathematicians ', Siam review, vol. 61, no. 4, pp. 860-891 . https://doi.org/10.1137/18M1165748
Multilayered artificial neural networks are becoming a pervasive tool in a host of application fields. At the heart of this deep learning revolution are familiar concepts from applied and computational mathematics, notably from calculus, approximatio
Publikováno v:
AI and Optical Data Sciences II.
Using a convolutional neural network to develop an optimal sampling strategy for LIDAR remote sensing. Detecting the distance to object is important for autonomous vehicles, surveying, and other remote sensing applications. LIDAR detects distances us
Autor:
Clara Cohen, Syed Waqar Nabi, Catherine F. Higham, Michael Putnam, Gerrit Jan Kootstra, Janet G. van Hell
Publikováno v:
Language. 97
Publikováno v:
Optical Sensing and Detection VI.
We present a prototype light detection and ranging (lidar) system that compressively samples the scene using our deep learning optimised sampling basis and reconstruction algorithms. This approach improves scene reconstruction quality compared to an
Autor:
Miles J. Padgett, Neal Radwell, Matthew P. Edgar, Steven D. Johnson, Catherine F. Higham, Roderick Murray-Smith
Publikováno v:
Conference on Lasers and Electro-Optics.
We present a LIDAR system that compressively samples a scene using a deeplearning optimised sampling basis and reconstruction algorithm. This approach improves scene reconstruction quality compared to an orthogonal sampling method.
Autor:
Katherine S. Panageas, Donavan T. Cheng, Michael F. Berger, Neal Rosen, Federica Catalanotti, Paul B. Chapman, Jeffrey A. Sosman, Taha Merghoub, David B. Solit, Parisa Momtaz, James J. Harding, Alexander N. Shoushtari, Helen Won, Catherine F. Higham, Douglas B. Johnson
Publikováno v:
JCO Precis Oncol
Purpose The clinical use of BRAF inhibitors in patients with melanoma is limited by intrinsic and acquired resistance. We asked whether next-generation sequencing of pretreatment tumors could identify coaltered genes that predict for intrinsic resist
Autor:
Matthew P. Edgar, Roderick Murray-Smith, Catherine F. Higham, Neal Radwell, Steven D. Johnson, Miles J. Padgett
Interest in autonomous transport has led to a demand for 3D imaging technologies capable of resolving fine details at long range. Light detection and ranging (LiDAR) systems have become a key technology in this area, with depth information typically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4757ce3cd0c22a325ada443ec729aedd
https://eprints.gla.ac.uk/203434/7/203434.pdf
https://eprints.gla.ac.uk/203434/7/203434.pdf