Results 211 to 220 of about 1,267,704 (337)

InBRwSANet: Self-attention based parallel inverted residual bottleneck architecture for human action recognition in smart cities. [PDF]

PLoS One
Jadoon YK, Khan MA, Khalid YN, Baili J, Bacanin N, Hong M, Nam Y.   +6 more
europepmc   +1 more source

Unsupervised non‐small cell lung cancer tumor segmentation using cycled generative adversarial network with similarity‐based discriminator

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning‐based automatic segmentation methods rely on manually annotated data for network training. Purpose This study aims to develop an unsupervised tumor segmentation network smic‐GAN by using a similarity‐driven generative adversarial ...
Chengyijue Fang, Xiaoyang Li, Yidong Yang   +2 more
wiley   +1 more source

Simulation of an octahedral random network by computer [PDF]

, 1987
Jean‐Marc Grenèche, J. Teillet, J. M. D. Coey   +2 more
openalex   +1 more source

Historians use data science to mine the past. [PDF]

Proc Natl Acad Sci U S A
Beans C.
europepmc   +1 more source

AAPM Task Group No. 249.B—Essentials and guidelines for clinical medical physics residency training program

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract The establishment of guidelines and curriculum standards for medical physics residency training is a critical component of setting expectations and competencies for the profession. Since the last publication of these standards, residency training has become integrated into the eligibility criteria for most medical physics certification bodies.
Jonathon A. Nye, Joseph P. Dugas, William D. Erwin, David P. Gierga, Darryl G. Kaurin, Stephanie M. Leon, Ho‐Ling Anthony Liu, Zheng Feng Lu, Alphonso W. Magri, Lynn N. Rill, Leah K. Schubert, Beth A. Schueler, Irina Vergalasova, John Vetter, Brian D. Wichman, Amy Shu‐Jung Yu, Dandan Zheng   +16 more
wiley   +1 more source

The computer science research network CSNET [PDF]

, 1983
Douglas E. Comer
openalex   +1 more source

Computation by neural networks [PDF]

Nature Neuroscience, 2000
openaire   +2 more sources

Image rain removal network based on checkerboard transformer and CNN hybrid mechanism. [PDF]

PLoS One
Yang Y, Lin J, Dai X, Zhang Z, Zhang S, Chen Y, Kong G, Li X.   +7 more
europepmc   +1 more source

UR‐cycleGAN: Denoising full‐body low‐dose PET images using cycle‐consistent Generative Adversarial Networks

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study aims to develop a CycleGAN based denoising model to enhance the quality of low‐dose PET (LDPET) images, making them as close as possible to standard‐dose PET (SDPET) images. Methods Using a Philips Vereos PET/CT system, whole‐body PET images of fluorine‐18 fluorodeoxyglucose (18F‐FDG) were acquired from 37 patients to ...
Yang Liu, ZhiWu Sun, HaoJia Liu
wiley   +1 more source