Results 71 to 80 of about 82,164 (262)

MaxViT: Multi-axis Vision Transformer

, 2022
ECCV 2022; code: https://github.com/google-research/maxvit v1: initials; v2: added GAN visuals; v3: fixed ImageNet-1k acc typos for Maxvit ...
Tu, Zhengzhong, Talebi, Hossein, Zhang, Han, Yang, Feng, Milanfar, Peyman, Bovik, Alan, Li, Yinxiao   +6 more
openaire   +2 more sources

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

Modeling Image Virality with Pairwise Spatial Transformer Networks

, 2017
The study of virality and information diffusion online is a topic gaining traction rapidly in the computational social sciences. Computer vision and social network analysis research have also focused on understanding the impact of content and information
Agarwal, Sumeet, Dubey, Abhimanyu
core   +1 more source

Vision Transformer With Quadrangle Attention

IEEE Transactions on Pattern Analysis and Machine Intelligence
Window-based attention has become a popular choice in vision transformers due to its superior performance, lower computational complexity, and less memory footprint. However, the design of hand-crafted windows, which is data-agnostic, constrains the flexibility of transformers to adapt to objects of varying sizes, shapes, and orientations.
Qiming Zhang, Jing Zhang, Yufei Xu, Dacheng Tao   +3 more
openaire   +3 more sources

Photonic Engineering Enables All‐Passive Upconversion Imaging with Low‐Intensity Near‐Infrared Light

Advanced Functional Materials, EarlyView.
A passive upconversion imaging system enables the observation of scenes illuminated by low‐intensity incoherent near‐infrared light from 750 to 930 nm, by converting it into the visible without the use of external power. The upconverter is enabled by triplet–triplet annihilation in a bulk heterojunction, with absorption enhanced by plasmonic resonators
Rabeeya Hamid, Demeng Feng, Pournima Narayanan, Justin S. Edwards, Manchen Hu, Emma Belliveau, Minjeong Kim, Shenwei Yin, Sanket Deshpande, Chenghao Wan, Linda Pucurimay, David A. Czaplewski, Daniel N. Congreve, Mikhail A. Kats   +13 more
wiley   +1 more source

Comparison Between CNN, ViT and CCT for Channel Frequency Response Interpretation and Application to G.Fast

IEEE Access, 2023
Convolutional Neural Networks (CNN) and more recently Visual Transformers (ViT) have been heavily used in specific areas like computer vision. Through this work, we explore and compare the CNNs and ViT models applied to a telecommunication signal, more ...
Philippe Dierickx, Axel Van Damme, Nicolas Dupuis, Olivier Delaby   +3 more
doaj   +1 more source

Designing Thermally Compatible Template‐Coating Pairs Toward Dimensionally Stable 3D Porous Carbons with Tunable Density

Advanced Functional Materials, EarlyView.
3D porous carbons with tunable density are crucial for energy storage, separations, and load‐bearing applications; however, their fabrication is often constrained by shrinkage during pyrolysis. This study optimizes and demonstrates the versatility of a template–coating pair strategy, producing materials that largely retain their shape and hierarchical ...
Adarsh Suresh, Manuela Campos, Kendrick Xie, Elektra Makris, Jonah Lovejoy, Maya El Shamsy, Chong Liu, Stuart J Rowan   +7 more
wiley   +1 more source

Transformers for Vision: A Survey on Innovative Methods for Computer Vision

IEEE Access
Transformers have emerged as a groundbreaking architecture in the field of computer vision, offering a compelling alternative to traditional convolutional neural networks (CNNs) by enabling the modeling of long-range dependencies and global context ...
Balamurugan Palanisamy, Vikas Hassija, Arpita Chatterjee, Arpita Mandal, Debanshi Chakraborty, Amit Pandey, G. S. S. Chalapathi, Dhruv Kumar   +7 more
doaj   +1 more source

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding

, 2018
Learning long-term dependencies in extended temporal sequences requires credit assignment to events far back in the past. The most common method for training recurrent neural networks, back-propagation through time (BPTT), requires credit information to ...
Bengio, Yoshua, Bilaniuk, Olexa, Binas, Jonathan, Goyal, Anirudh, Ke, Nan Rosemary, Mozer, Michael C., Pal, Chris   +6 more
core   +1 more source

Upconversion Nanoparticles Embedded Photonic Contact Lens for Transepithelial Corneal Crosslinking Using Hyaluronate – Riboflavin Conjugate

Advanced Functional Materials, EarlyView.
A minimally invasive, transepithelial corneal cross‐linking (TE‐CXL) approach is presented using upconversion nanoparticles (UCNPs)‐loaded contact lenses (UCLs), after topical delivery of hyaluronate–riboflavin conjugates. The NIR‐to‐UV/blue light conversion by UCNPs in a UCL can activate riboflavin for TE‐CXL, resulting in the biomechanical strength ...
Gibum Lee, Inhoo Choi, Anara Molkenova, Yengwoo Son, Seungmin Yang, Mina Kwon, Tae‐Im Kim, Ki Su Kim, Sei Kwang Hahn   +8 more
wiley   +1 more source