[PDF] Top 20 2020 — Modeling information flow through deep convolutional neural networks
Has 10000 "2020 — Modeling information flow through deep convolutional neural networks" found on our website. Below are the top 20 most common "2020 — Modeling information flow through deep convolutional neural networks".
2020 — Modeling information flow through deep convolutional neural networks
... optimizing deep convolutional neural networks (CNN) by 1) reducing the computational complexity and 2) improving classification performance for the task of transfer ...accuracy. ... Voir le document complet
180
Classification of Time-Series Images Using Deep Convolutional Neural Networks
... trajectory through a 2D representation of its ...typology information which are characterized as homogeneous, periodic, drift and ...and information in RP that are ... Voir le document complet
9
Geodesic Convolutional Neural Network for 3D Deep-Learning based Surrogate Modeling and Optimization
... of Neural Concept Shape (NCS), a surrogate modelling software that proposes using geodesic deep neural networks as regressors to overcome the aforementioned limitations of Gaussian Process ... Voir le document complet
2
Convolutional neural networks for atomistic systems
... done through the use of convolutional layers. A convolutional layer consists of a set of kernels (matrices) which contain adjustable ...a convolutional layer, the operation produces a ... Voir le document complet
23
Learning to recognise 3D human action from a new skeleton-based representation using deep convolutional neural networks
... on deep learning: Recurrent Neural Networks with Long Short-Term Memory Network (RNN-LSTMs) [ 42 , 43 ] are able to model the contextual information of the temporal sequences as skeleton ... Voir le document complet
12
Classification of Time-Series Images Using Deep Convolutional Neural Networks
... trajectory through a 2D representation of its ...typology information which are characterized as homogeneous, periodic, drift and ...and information in RP that are ... Voir le document complet
9
Predicting the Propagation of Acoustic Waves using Deep Convolutional Neural Networks
... Multi-Scale convolutional neural network trained on LBM-generated ...studied through the variation of loss ...Both networks are then evaluated with initial conditions unseen during the ... Voir le document complet
19
Learning Activation Functions in Deep Neural Networks
... of deep neural networks (deep learning) achieved considerable success in pattern recognition and text ...of deep learning on images, video or text classification, the application of ... Voir le document complet
171
Lip Reading with Hahn Convolutional Neural Networks moments
... for modeling the sequences and uses very deep pre-defined CNN architecture such as GoogleNet, AlexNet and Net- work in Network (NIN) for the recognition ... Voir le document complet
28
Deep neural networks for choice analysis
... travel behavior through the change of tolls or subsidies [118, 53]. VOT, as one impor- tant instance of MRS, can be used to measure the monetary gain of saved time after the improvement of a transportation system ... Voir le document complet
128
Emotion Recognition with Deep Neural Networks
... “Recurrent Neural Networks for Emotion Recognition in Video” (Ebrahimi Kahou et ...sequential modeling using an ...preserve information about temporal ordering of detected ... Voir le document complet
145
Bandwidth extension of musical audio signals with no side information using dilated convolutional neural networks
... Reverting to the time domain requires the estimation of the phase information for higher frequencies whose magni- tude have been predicted. Several methods proposed in the literature are considered. For evaluation ... Voir le document complet
6
Biological Sequence Modeling with Convolutional Kernel Networks
... sequence modeling [Alipanahi et ...regularizing neural networks to avoid overfitting is another open issue and involves various heuristics such as dropout [Srivastava et ...training neural ... Voir le document complet
28
Spatio-temporal convolutional neural networks for failure prediction
... [2] F. Rosenblatt, “The perceptron–a perceiving and re- cognizing automaton,” Tech. Rep. 85-460-1, Cornell Aeronautical Laboratory, 1957. [3] M. Negnevitsky, Artificial Intelligence : A Guide to Intelligent Systems. ... Voir le document complet
5
Relating images and 3D models with convolutional neural networks
... high-level information from images, but it is unclear whether they can directly be used in such disparate domains, or if substantial modi cations to these features are ... Voir le document complet
136
High-Resolution Semantic Labeling with Convolutional Neural Networks
... level information, with how another layer evaluates whether the same object is a building by using higher-level ...use deep multi-layer schemes with down- sampling because we actually consider that certain ... Voir le document complet
14
Creating Synthetic Radar Imagery Using Convolutional Neural Networks
... S U P E R C O M P U T I N G C E N T E R The figure on the left shows precipitation intensity, with lightning flashes as white plus symbols in the area outside the coverage of weather radar. By comparison, on the right ... Voir le document complet
2
Robust parallel-gripper grasp getection using convolutional neural networks
... two networks, but this was found to be non-trivial, as their proposed method is meant as a two-step ...Using Convolutional Neural Networks” (Joseph Red- mon and Angelova, 2015 ), presented in ... Voir le document complet
84
Robust detection of astronomical sources using convolutional neural networks
... Received 18 July 2019 / Accepted 9 December 2019 ABSTRACT In this work, we propose two convolutional neural network classifiers for detecting contaminants in astronomical images. Once trained, our ... Voir le document complet
229
Convolutional Neural Fabrics
... Stitching convolutional neural networks on the fabric We now demonstrate how various architectural choices can be “implemented” in fabrics, demonstrat- ing they subsume an exponentially large class ... Voir le document complet
15
Sujets connexes