Zobrazeno 1 - 10
of 16 522
pro vyhledávání: '"Are Dalen"'
Automatic speech recognition (ASR) with an encoder equipped with self-attention, whether streaming or non-streaming, takes quadratic time in the length of the speech utterance. This slows down training and decoding, increase their cost, and limit the
Externí odkaz:
http://arxiv.org/abs/2409.07165
Autor:
Van De Vyver, Gilles, Måsøy, Svein-Erik, Dalen, Håvard, Grenne, Bjørnar Leangen, Holte, Espen, Olaisen, Sindre Hellum, Nyberg, John, Østvik, Andreas, Løvstakken, Lasse, Smistad, Erik
Automatic estimation of cardiac ultrasound image quality can be beneficial for guiding operators and ensuring the accuracy of clinical measurements. Previous work often fails to distinguish the view correctness of the echocardiogram from the image qu
Externí odkaz:
http://arxiv.org/abs/2408.00591
Autor:
Dockery, Dalen
In 2016, Ahlgren and Samart used the theory of holomorphic modular forms to obtain lower bounds on $p$-adic valuations related to the Fourier coefficients of three cusp forms. In particular, their work strengthened a previous result of El-Guindy and
Externí odkaz:
http://arxiv.org/abs/2407.19374
Self-supervised learning (SSL) models usually require weeks of pre-training with dozens of high-end GPUs. These models typically have a multi-headed self-attention (MHSA) context encoder. However, MHSA takes quadratic time and space in the input leng
Externí odkaz:
http://arxiv.org/abs/2407.13377
Autor:
Azad, Md Abulkalam, Chernyshov, Artem, Nyberg, John, Tveten, Ingrid, Lovstakken, Lasse, Dalen, Håvard, Grenne, Bjørnar, Østvik, Andreas
Tissue tracking in echocardiography is challenging due to the complex cardiac motion and the inherent nature of ultrasound acquisitions. Although optical flow methods are considered state-of-the-art (SOTA), they struggle with long-range tracking, noi
Externí odkaz:
http://arxiv.org/abs/2405.08587
Autor:
Xu, Jie, Saravanan, Karthikeyan, van Dalen, Rogier, Mehmood, Haaris, Tuckey, David, Ozay, Mete
Federated learning (FL) allows clients to collaboratively train a global model without sharing their local data with a server. However, clients' contributions to the server can still leak sensitive information. Differential privacy (DP) addresses suc
Externí odkaz:
http://arxiv.org/abs/2405.06368
Autor:
Shvetsov, Nikita, Sildnes, Anders, Busund, Lill-Tove Rasmussen, Dalen, Stig, Møllersen, Kajsa, Bongo, Lars Ailo, Kilvaer, Thomas K.
Addressing the critical need for accurate prognostic biomarkers in cancer treatment, quantifying tumor-infiltrating lymphocytes (TILs) in non-small cell lung cancer (NSCLC) presents considerable challenges. Manual TIL quantification in whole slide im
Externí odkaz:
http://arxiv.org/abs/2405.02913
Autor:
Levan, Andrew J., Jonker, Peter G., Saccardi, Andrea, Malesani, Daniele Bjørn, Tanvir, Nial R., Izzo, Luca, Heintz, Kasper E., Sánchez, Daniel Mata, Quirola-Vásquez, Jonathan, Torres, Manuel A. P., Vergani, Susanna D., Schulze, Steve, Rossi, Andrea, D'Avanzo, Paolo, Gompertz, Benjamin, Martin-Carrillo, Antonio, Postigo, Antonio de Ugarte, Schneider, Benjamin, Yuan, Weimin, Ling, Zhixing, Zhang, Wenjie, Mao, Xuan, Liu, Yuan, Sun, Hui, Xu, Dong, Zhu, Zipei, Fernández, José Feliciano Agüí, Amati, Lorenzo, Bauer, Franz E., Campana, Sergio, Carotenuto, Francesco, Chrimes, Ashley, van Dalen, Joyce N. D., D'Elia, Valerio, Della Valle, Massimo, De Pasquale, Massimiliano, Dhillon, Vikram S., Galbany, Lluís, Gaspari, Nicola, Gianfagna, Giulia, Gomboc, Andreja, Habeeb, Nusrin, van Hoof, Agnes P. C., Hu, Youdong, Jakobsson, Pall, Julakanti, Yashaswi, Korth, Judith, Kouveliotou, Chryssa, Laskar, Tanmoy, Littlefair, Stuart P., Maiorano, Elisabetta, Mao, Jirong, Melandri, Andrea, Miller, M. Coleman, Mukherjee, Tamal, Oates, Samantha R., O'Brien, Paul, Palmerio, Jesse T., Parviainen, Hannu, Pieterse, Daniëlle L. A., Piranomonte, Silvia, Piro, Luigi, Pugliese, Giovanna, Ravasio, Maria E., Rayson, Ben, Salvaterra, Ruben, Sánchez-Ramírez, Rubén, Sarin, Nikhil, Shilling, Samuel P. R., Starling, Rhaana L. C., Tagliaferri, Gianpiero, Thakur, Aishwarya Linesh, Thöne, Christina C., Wiersema, Klaas, Worssam, Isabelle, Zafar, Tayyaba
The nature of the minute-to-hour long Fast X-ray Transients (FXTs) localised by telescopes such as Chandra, Swift, and XMM-Newton remains mysterious, with numerous models suggested for the events. Here, we report multi-wavelength observations of EP24
Externí odkaz:
http://arxiv.org/abs/2404.16350
Autor:
Granqvist, Filip, Song, Congzheng, Cahill, Áine, van Dalen, Rogier, Pelikan, Martin, Chan, Yi Sheng, Feng, Xiaojun, Krishnaswami, Natarajan, Jina, Vojta, Chitnis, Mona
Federated learning (FL) is an emerging machine learning (ML) training paradigm where clients own their data and collaborate to train a global model, without revealing any data to the server and other participants. Researchers commonly perform experim
Externí odkaz:
http://arxiv.org/abs/2404.06430
Autor:
Fermann, Benjamin Strandli, Nyberg, John, Remme, Espen W., Grue, Jahn Frederik, Grue, Helén, Håland, Roger, Lovstakken, Lasse, Dalen, Håvard, Grenne, Bjørnar, Aase, Svein Arne, Snar, Sten Roar, Østvik, Andreas
Cardiac valve event timing plays a crucial role when conducting clinical measurements using echocardiography. However, established automated approaches are limited by the need of external electrocardiogram sensors, and manual measurements often rely
Externí odkaz:
http://arxiv.org/abs/2403.10156