Results 111 to 120 of about 2,004,297 (387)
Kernel-based Translations of Convolutional Networks [PDF]
arXiv, 2019 Convolutional Neural Networks, as most artificial neural networks, are commonly viewed as methods different in essence from kernel-based methods. We provide a systematic translation of Convolutional Neural Networks (ConvNets) into their kernel-based counterparts, Convolutional Kernel Networks (CKNs), and demonstrate that this perception is unfounded ...
arxiv
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 +11 more
wiley +1 more source
Occupational Therapy International, 2022 In this paper, we construct a model of convolutional neural network speech emotion algorithm, analyze the classroom identified by the neural network with a certain degree of confidence together with the school used in the dataset, find the ...
Qinying Yuan
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
Quaternion Convolutional Neural Networks [PDF]
, 2018 Neural networks in the real domain have been studied for a long time and achieved promising results in many vision tasks for recent years. However, the extensions of the neural network models in other number fields and their potential applications are not fully-investigated yet. Focusing on color images, which can be naturally represented as quaternion
Changjian Chen +3 more
openaire +3 more sources
Advanced Biology, EarlyView.Synthetic cells (SCs) hold great promise for biomedical applications, but manual production limits scalability. This study presents an automated method for large‐scale SC synthesis, integrating robotic liquid handling and machine learning‐driven high‐throughput characterization.
Noga Sharf‐Pauker +7 more
wiley +1 more source
Isointense infant brain MRI segmentation with a dilated convolutional neural network [PDF]
, 2017 Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D ...
Moeskops, Pim, Pluim, Josien P. W.
core +2 more sources
One weird trick for parallelizing convolutional neural networks [PDF]
arXiv, 2014 I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional neural networks.
arxiv
Powerset Convolutional Neural Networks
, 2019 We present a novel class of convolutional neural networks (CNNs) for set functions, i.e., data indexed with the powerset of a finite set. The convolutions are derived as linear, shift-equivariant functions for various notions of shifts on set functions.
Wendler, Chris +2 more
openaire +3 more sources
Ontologies for FAIR Data in Additive Manufacturing: A Use Case‐Based Evaluation
Advanced Engineering Materials, EarlyView.An ontology‐based approach for generating findable, accessible, interoperable, reusable data in additive manufacturing is explored, focusing on powder bed fusion. The article highlights the benefits of enhanced data findability and digital twin enablement, while addressing challenges like data integration complexity and the need for specialized ...
Thomas Bjarsch +2 more
wiley +1 more source