Zobrazeno 1 - 10
of 433
pro vyhledávání: '"Yezzi, Anthony"'
Autor:
Wang, Zuowen, Gao, Chang, Wu, Zongwei, Conde, Marcos V., Timofte, Radu, Liu, Shih-Chii, Chen, Qinyu, Zha, Zheng-jun, Zhai, Wei, Han, Han, Liao, Bohao, Wu, Yuliang, Wan, Zengyu, Wang, Zhong, Cao, Yang, Tan, Ganchao, Chen, Jinze, Pei, Yan Ru, Brüers, Sasskia, Crouzet, Sébastien, McLelland, Douglas, Coenen, Oliver, Zhang, Baoheng, Gao, Yizhao, Li, Jingyuan, So, Hayden Kwok-Hay, Bich, Philippe, Boretti, Chiara, Prono, Luciano, Lică, Mircea, Dinucu-Jianu, David, Grîu, Cătălin, Lin, Xiaopeng, Ren, Hongwei, Cheng, Bojun, Zhang, Xinan, Vial, Valentin, Yezzi, Anthony, Tsai, James
This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge. The task of the challenge focuses on processing eye movement recorded with event cameras and predicting the pupil center of the eye. The challenge emphasizes efficient eye tra
Externí odkaz:
http://arxiv.org/abs/2404.11770
We present new insights and a novel paradigm (StEik) for learning implicit neural representations (INR) of shapes. In particular, we shed light on the popular eikonal loss used for imposing a signed distance function constraint in INR. We show analyt
Externí odkaz:
http://arxiv.org/abs/2305.18414
We discover restrained numerical instabilities in current training practices of deep networks with stochastic gradient descent (SGD), and its variants. We show numerical error (on the order of the smallest floating point bit and thus the most extreme
Externí odkaz:
http://arxiv.org/abs/2206.02001
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 45, No. 7, pp. 8372-8389, July 2023
Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences asynchronously. Recovering brightness from events is appealing since the reconstructed images inherit the high dynamic range (HDR) and high-speed properties of
Externí odkaz:
http://arxiv.org/abs/2112.06242
Deep learning (DL) 3D dose prediction has recently gained a lot of attention. However, the variability of plan quality in the training dataset, generated manually by planners with wide range of expertise, can dramatically effect the quality of the fi
Externí odkaz:
http://arxiv.org/abs/2106.03705
Autor:
Yezzi, Anthony
We examine the optimal mass transport problem in $\mathbb{R}^{n}$ between densities having independent compact support by considering the geometry of a continuous interpolating support boundary in space-time within which the mass density evolves acco
Externí odkaz:
http://arxiv.org/abs/2105.12300
If we wish to integrate a function $h|\Omega\subset\Re^{n}\to\Re$ along a single $T$-level surface of a function $\psi |\Omega\subset\Re^{n}\to\Re$, then a number of different methods for extracting finite elements appropriate to the dimension of the
Externí odkaz:
http://arxiv.org/abs/2103.14926
This paper proposes a novel training model based on shape and appearance features for object segmentation in images and videos. Whereas most such models rely on two-dimensional appearance templates or a finite set of descriptors, our appearance-based
Externí odkaz:
http://arxiv.org/abs/2103.14887
Autor:
Dahiya, Navdeep, Alam, Sadegh R, Zhang, Pengpeng, Zhang, Si-Yuan, Yezzi, Anthony, Nadeem, Saad
In current clinical practice, noisy and artifact-ridden weekly cone-beam computed tomography (CBCT) images are only used for patient setup during radiotherapy. Treatment planning is done once at the beginning of the treatment using high-quality plann
Externí odkaz:
http://arxiv.org/abs/2103.05690
The robustness of neural networks is challenged by adversarial examples that contain almost imperceptible perturbations to inputs, which mislead a classifier to incorrect outputs in high confidence. Limited by the extreme difficulty in examining a hi
Externí odkaz:
http://arxiv.org/abs/2010.09633