Results 111 to 120 of about 1,028,974 (354)

Convolutional Oriented Boundaries [PDF]

, 2016
We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs). COB is computationally efficient, because it requires a single CNN forward pass for contour detection and it uses a novel sparse boundary representation ...
Jordi Pont-Tuset, Kevis-Kokitsi Maninis, Luc Van Gool, Luc Van Gool, Pablo Arbeláez   +4 more
openaire   +4 more sources

Stereotactic radiotherapy for metastatic brain tumors: A comparative analysis of dose distributions among VMAT, Helical TomoTherapy, CyberKnife, Gamma Knife, and ZAP‐X

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract This study evaluates various radiotherapy techniques for treating metastatic brain tumor (BT), focusing on non‐coplanar volumetric modulated arc radiotherapy (NC‐VMAT), coplanar VMAT (C‐VMAT), Helical TomoTherapy (HT), CyberKnife (CK), Gamma Knife (GK), and ZAP‐X.
Toshihiro Suzuki, Masahide Saito, Ryutaro Nomura, Hikaru Nemoto, Naoto Yanagisawa, Ryuma Sawada, Zennosuke Mochizuki, Naoki Sano, Hiroshi Onishi, Hiroshi Takahashi   +9 more
wiley   +1 more source

Sufficiency criteria for a class of convex functions connected with tangent function

AIMS Mathematics
The research here was motivated by a number of recent studies on Hankel inequalities and sharp bounds. In this article, we define a new subclass of holomorphic convex functions that are related to tangent functions.
Muhammad Ghaffar Khan, Sheza.M. El-Deeb, Daniel Breaz , Wali Khan Mashwani , Bakhtiar Ahmad   +4 more
doaj   +1 more source

Revised fast convolution

Lietuvos Matematikos Rinkinys, 2016
It is assumed that linear time-invariant (LTI) system input signal samples are updated by a sensor in real time. It is urgent for every new input sample or for small part of new samples to update a convolution as well.
Rimantas Pupeikis
doaj   +1 more source

Convolutional Neural Networks In Convolution

, 2018
Currently, increasingly deeper neural networks have been applied to improve their accuracy. In contrast, We propose a novel wider Convolutional Neural Networks (CNN) architecture, motivated by the Multi-column Deep Neural Networks and the Network In Network(NIN), aiming for higher accuracy without input data transmutation.
openaire   +2 more sources

Geometric and dosimetric evaluation of a commercial AI auto‐contouring tool on multiple anatomical sites in CT scans

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Current radiotherapy practices rely on manual contouring of CT scans, which is time‐consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto‐contouring tool to assess its potential integration into
Robert N. Finnegan, Alexandra Quinn, Patrick Horsley, Joseph Chan, Maegan Stewart, Regina Bromley, Jeremy Booth   +6 more
wiley   +1 more source

Partial Label Learning With Focal Loss for Sea Ice Classification Based on Ice Charts

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Sea ice, crucial to the Arctic and Earth's climate, requires consistent monitoring and high-resolution mapping. Manual sea ice mapping, however, is time-consuming and subjective, prompting the need for automated deep learning-based classification ...
Behzad Vahedi, Benjamin Lucas, Farnoush Banaei-Kashani, Andrew P. Barrett, Walter N. Meier, Siri Jodha Singh Khalsa, Morteza Karimzadeh   +6 more
doaj   +1 more source

Dosimetric effect of silicone‐based gel on skin surface during volumetric modulated arc therapy for breast cancer

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study aims to quantify and compare the dosimetric effects of varying thicknesses of StrataXRT, a silicone‐based gel, and other topical agents on the skin surface during volumetric modulated arc therapy (VMAT) for breast cancer.
Tenyoh Suzuki, Shingo Ohira, Mami Ogita, Takeshi Ohta, Yuki Nozawa, Masanari Minamitani, Takuya Hayashi, Shigeki Saegusa, Toshikazu Imae, Tsuyoshi Ueyama, Atsuto Katano, Hideomi Yamashita, Weishan Chang, Keiichi Nakagawa   +13 more
wiley   +1 more source

CR‐Net: Robot grasping detection method integrating convolutional block attention module and residual module

IET Computer Vision
Grasping detection, which involves identifying and assessing the grasp ability of objects by robotic systems, has garnered significant attention in recent years due to its pivotal role in the development of robotic systems and automated assembly ...
Song Yan, Lei Zhang
doaj   +1 more source

TransConv: Transformer Meets Contextual Convolution for Unsupervised Domain Adaptation

Entropy
Unsupervised domain adaptation (UDA) aims to reapply the classifier to be ever-trained on a labeled source domain to a related unlabeled target domain. Recent progress in this line has evolved with the advance of network architectures from convolutional ...
Junchi Liu, Xiang Zhang, Zhigang Luo
doaj   +1 more source