Results 171 to 180 of about 52,085 (312)

Sim-to-real domain adaptation based completion level recognition for autonomous micro-drilling in biomedical application. [PDF]

Sci Rep
Zhao E, Perez SAH, Harada K.
europepmc   +1 more source

Efficient Training of Convolutional Neural Nets on Large Distributed\n Systems [PDF]

, 2017
Sameer Kumar, Dheeraj Sreedhar, Vaibhav Saxena, Yogish Sabharwal, Ashish Verma   +4 more
openalex   +1 more source

Convolution Neural Networks by Image Net

International Journal of Emerging Trends in Science and Technology, 2017
openaire   +1 more source

Deformation Prediction of 4D‐Printed Active Composite Structures Based on Data Mining

Advanced Science, EarlyView.
A curvature‐driven sequence point generation (CSPG) algorithm based on data mining is proposed to predict the deformation of double‐layer voxelized composite structures of arbitrary lengths. In addition, the CSPG algorithm is applied to predict the deformation of 2D and 3D structures assembled from beam elements, and its effectiveness is validated ...
Mengtao Wang, Yifan Xu, Zaiyang Liu, Hidemitsu Furukawa, Zhongkui Wang, Ren Xu, Lin Meng   +6 more
wiley   +1 more source

Automated detection of wrist ganglia in MRI using convolutional neural networks. [PDF]

BMC Musculoskelet Disord
Hämäläinen M, Sormaala M, Kaseva T, Salli E, Savolainen S, Kangasniemi M.   +5 more
europepmc   +1 more source

Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field [PDF]

R Pearce-Casey, B.C Nagam, J. Wilde, Valerio Busillo, L. Ulivi, I.T Andika, A Manjón-García, Laura Leuzzi, Predrag Matavulj, S. Serjeant, Mike Walmsley, J.A. Acevedo Barroso, Colm O’Riordan, Benjamin Clément, C. Tortora, T.E Collett, F. Courbin, R. Gavazzi, R. B. Metcalf, R. Cabanac, H.M Courtois, J Crook-Mansour, L. Delchambre, Giulia Despali, L.R Ecker, A Franco, Paul H. Holloway, K. Jahnkę, Guillaume Mahler, L. Marchetti, Andréia Cristina de Melo, M. Meneghetti, Oliver Müller, Achille Nucita, J. C. Pearson, K. Rojas, Claudia Scarlata, S. Schuldt, Dominique Sluse, S. H. Suyu, M. Vaccari, Simona Vegetti, A. Verma, G. Vernardos, M. Bolzonella, Matthias Kluge, T. Saifollahi, M Schirmer, Christopher Stone, Ana Paulino-Afonso, L. Bazzanini, Natalie B Hogg, L. V. E. Koopmans, Sandor Kruk, F. Mannucci, J. Bromley, A. Díaz‐Sánchez, L. Fortson, D.M Powell, H. Bouy, R. Laureijs, B. Altieri, A. Amara, S Andreon, C. Baccigalupi, M Baldi, A. Balestra, S. Bardelli, S Bardelli, D. Bonino, E. Branchini, M. Brescia, J. Brinchmann, A. Caillat, S. Camera, V. Capobianco, C. Carbone, J. Carretero, Santiago Casas, M. Castellano, G Castignani, S. Cavuoti, A. Cimatti, C Colodro-Conde, G. Congedo, Christopher J. Conselice, L Conversi, Y. Copin, M. Cropper, A. Da Silva, H. Degaudenzi, G. De Lucia, A. M. Di Giorgio, J. Dinis, F. Dubath, X Dupac, S Dusini, M. Farina, S. Farrens, F Faustini   +99 more
openalex   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

The principles behind equivariant neural networks for physics and chemistry. [PDF]

Proc Natl Acad Sci U S A
Kondor R.
europepmc   +1 more source

DeepSat V2: feature augmented convolutional neural nets for satellite image classification [PDF]

, 2019
Qun Liu, Saikat Basu, Sangram Ganguly, Supratik Mukhopadhyay, Robert DiBiano, Manohar Karki, Ramakrishna Nemani   +6 more
openalex   +1 more source

Biomimetic Multiscale‐Structured Biomass Graphene/Polyurethane Sponge Composite for Flexible Pressure Sensors and Intelligent Cushioning Materials

Advanced Science, EarlyView.
In this study, a multifunctional conductive sponge composite (MAPU) is developed using a biomimetic, hierarchical construction strategy emulating the growth process of natural wood. This approach involved integrating biomass‐derived graphitic nanoflakes, synthesized from luffa vine (LVGN), into a polyurethane (PU) sponge matrix.
Runmin Xu, Pusen Cao, Tingting Zhang, Jie Wei, Yue Wang, Zhi Huang, Zhenghang Chen, Jianfeng Xi, Yong Guo, Yuxia Chen   +9 more
wiley   +1 more source