Results 111 to 120 of about 7,675,115 (371)

The rebirth of neural networks [PDF]

Proceedings of the 37th annual international symposium on Computer architecture, 2010
After the hype of the 1990s, where companies like Intel or Philips built commercial hardware systems based on neural networks, the approach quickly lost ground for multiple reasons: hardware neural networks were no match for software neural networks run on rapidly progressing general-purpose processors, their application scope was considered too ...
openaire   +3 more sources

Toward a human‐centric co‐design methodology for AI detection of differences between planned and delivered dose in radiotherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Introduction Many artificial intelligence (AI) solutions have been proposed to enhance the radiotherapy (RT) workflow, but limited applications have been implemented to date, suggesting an implementation gap. One contributing factor to this gap is a misalignment between AI systems and their users.
Luca M. Heising, Frank Verhaegen, Stefan G. Scheib, Maria J. G. Jacobs, Carol X. J. Ou, Viola Mottarella, Yin‐Ho Chong, Mariangela Zamburlini, Sebastiaan M. J. J. G. Nijsten, Ans Swinnen, Michel Öllers, Cecile J. A. Wolfs   +11 more
wiley   +1 more source

Efficient musculoskeletal annotation using free-form deformation

Scientific Reports
Traditionally, constructing training datasets for automatic muscle segmentation from medical images involved skilled operators, leading to high labor costs and limited scalability.
Norio Fukuda, Shoji Konda, Jun Umehara, Masaya Hirashima   +3 more
doaj   +1 more source

Cortex Neural Network: learning with Neural Network groups [PDF]

arXiv, 2018
Neural Network has been successfully applied to many real-world problems, such as image recognition and machine translation. However, for the current architecture of neural networks, it is hard to perform complex cognitive tasks, for example, to process the image and audio inputs together. Cortex, as an important architecture in the brain, is important
arxiv  

Neural Networks Architecture Evaluation in a Quantum Computer [PDF]

, 2017
In this work, we propose a quantum algorithm to evaluate neural networks architectures named Quantum Neural Network Architecture Evaluation (QNNAE). The proposed algorithm is based on a quantum associative memory and the learning algorithm for artificial neural networks.
arxiv   +1 more source

Generating Neural Networks with Neural Networks

, 2018
Hypernetworks are neural networks that generate weights for another neural network. We formulate the hypernetwork training objective as a compromise between accuracy and diversity, where the diversity takes into account trivial symmetry transformations of the target network. We explain how this simple formulation generalizes variational inference.
openaire   +2 more sources

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

Parametrical Neural Networks and Some Other Similar Architectures [PDF]

arXiv, 2006
A review of works on associative neural networks accomplished during last four years in the Institute of Optical Neural Technologies RAS is given. The presentation is based on description of parametrical neural networks (PNN). For today PNN have record recognizing characteristics (storage capacity, noise immunity and speed of operation).
arxiv  

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

Progressive Myoclonus Epilepsy: Distinctive MRI Changes in Cerebellar and Motor Networks

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progressive myoclonus epilepsy (PME) is a rare generalized epilepsy syndrome with a well‐characterized genetic basis. The brain networks that are affected to give rise to the distinctive symptoms of PME are less well understood. Methods Eleven individuals with PME with a confirmed genetic diagnosis and 22 controls were studied.
Jillian M. Cameron, Remika Mito, Samuel F. Berkovic, Graeme D. Jackson   +3 more
wiley   +1 more source