Results 81 to 90 of about 60,311 (308)

Continuum Robots in Surgery: From Engineering Design to Clinical Practice

Advanced Robotics Research, EarlyView.
The hyper‐redundant nature of continuum robot structures enables near‐infinite degrees of freedom leading to immense potential for medical applications. This review provides a historical background of continuum robots and novel ideas shaping their progress to current structural design, sensing technology, modeling techniques, and control methods.
Griffin Smith, Kaitlyn Clancy, Siwen Xie, Xiaochen Li, Sarah Khalife, Benjamin van der Woerd, Onaizah Onaizah   +6 more
wiley   +1 more source

Zooming Into Clarity: Image Denoising Through Innovative Autoencoder Architectures

IEEE Access
In today’s era of increasing data complexity and pervasive noise, robust techniques for data processing, reconstruction, and denoising are crucial.
Khatereh Mohammadi, Ashhadul Islam, Samir Brahim Belhaouari   +2 more
doaj   +1 more source

A quantum autoencoder: using machine learning to compress qutrits

, 2020
The compression of quantum data will allow increased control over difficult-to- manage quantum resources. We experimentally realize a quantum autoencoder, which learns to compress quantum data with a classical machine learning routine.Full ...
Geoff J. Pryde, Tischler, N, Nora Tischler, Alex Pepper, Pryde, GJ, Pepper, A   +5 more
core   +1 more source

TacVerse: A Multisensor Dataset and Benchmark for Cross‐Sensor Vision‐Based Tactile Perception

Advanced Robotics Research, EarlyView.
TacVerse provides a controlled benchmark of 106 800 tactile images from seven vision‐based tactile sensors across shape classification, grating classification, and force regression. Direct cross‐sensor transfer reveals substantial sensor‐shift degradation, with grating and force perception more affected than shape recognition.
Lan Wei, Gurmeher Khurana, Sirine Bhouri, Wenhao Hong, Zeyuan Xin, Qingzheng Cong, Wen Fan, Yanzheng Xiang, Dandan Zhang   +8 more
wiley   +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

Toroidal AutoEncoder

CoRR, 2019
Enforcing distributions of latent variables in neural networks is an active subject. It is vital in all kinds of generative models, where we want to be able to interpolate between points in the latent space, or sample from it. Modern generative AutoEncoders (AE) like WAE, SWAE, CWAE add a regularizer to the standard (deterministic) AE, which allows to ...
Maciej Mikulski, Jaroslaw Duda 0001
openaire   +3 more sources

Glaucoma detection in myopic eyes using deep learning autoencoder-based regions of interest

Frontiers in Ophthalmology
PurposeTo evaluate the diagnostic accuracy of a deep learning autoencoder-based model utilizing regions of interest (ROI) from optical coherence tomography (OCT) texture enface images for detecting glaucoma in myopic eyes.MethodsThis cross-sectional ...
Christopher Bowd, Akram Belghith, Mark Christopher, Makoto Araie, Aiko Iwase, Goji Tomita, Kyoko Ohno-Matsui, Hitomi Saito, Hiroshi Murata, Tsutomu Kikawa, Kazuhisa Sugiyama, Tomomi Higashide, Atsuya Miki, Atsuya Miki, Toru Nakazawa, Makoto Aihara, Tae-Woo Kim, Christopher Kai Shun Leung, Robert N. Weinreb, Linda M. Zangwill   +19 more
doaj   +1 more source

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

Advanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li, Kelly Yichen Li, Chiara Nicoletti, Stephen Kwok‐Wing Tsui, Pier Lorenzo Puri, Qin Cao, Kevin Y. Yip   +6 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Autoencoding any Data through Kernel Autoencoders

CoRR, 2018
This paper investigates a novel algorithmic approach to data representation based on kernel methods. Assuming that the observations lie in a Hilbert space X, the introduced Kernel Autoencoder (KAE) is the composition of mappings from vector-valued Reproducing Kernel Hilbert Spaces (vv-RKHSs) that minimizes the expected reconstruction error.
Pierre Laforgue, Stéphan Clémençon, Florence d'Alché-Buc   +2 more
openaire   +4 more sources