Results 71 to 80 of about 367,129 (284)

Challenges in Representation Learning: A report on three machine learning contests

, 2013
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge.
Athanasakis, Dimitris, Bengio, Yoshua, Bergstra, James, Carrier, Pierre Luc, Chuang, Zhang, Courville, Aaron, Cukierski, Will, Erhan, Dumitru, Feng, Fangxiang, Goodfellow, Ian J., Grozea, Cristian, Hamner, Ben, Ionescu, Radu, Lee, Dong-Hyun, Li, Ruifan, Milakov, Maxim, Mirza, Mehdi, Park, John, Popescu, Marius, Ramaiah, Chetan, Romaszko, Lukasz, Shawe-Taylor, John, Tang, Yichuan, Thaler, David, Wang, Xiaojie, Xie, Jingjing, Xu, Bing, Zhou, Yingbo   +27 more
core   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Learners’ continuance intention in multimodal language learning education: An innovative multiple linear regression model

Heliyon
Confronted with the unprecedented COVID-19 pandemic, millions of learners have received, are receiving, or will receive multimodal language learning education.
Yan Huang, Wei Xu, Paisan Sukjairungwattana, Zhonggen Yu   +3 more
doaj   +1 more source

Reggio Emilia and the arts approach: Two exceptional examples of multimodal learning in early years

Journal of Global Education and Research, 2019
The Reggio Emilia approach offers children a unique experience of self-exploration embedded in the arts. This has strong links with multimodal teaching and learning.
Fadumo Aden, Evgenia Theodotou
doaj   +1 more source

Deep Multimodal Representation Learning from Temporal Data

, 2017
In recent years, Deep Learning has been successfully applied to multimodal learning problems, with the aim of learning useful joint representations in data fusion applications.
Bernal, Edgar A., Chitta, Radha, Luo, Jiebo, Madhvanath, Sriganesh, Ramesh, Palghat, Yang, Xitong   +5 more
core   +1 more source

Multimodal Conception in Learning

ISLLAC : Journal of Intensive Studies on Language, Literature, Art, and Culture, 2018
This article aims to formulate a multimodal conception in the learning hierarchy. This exposure is based on three things, namely: (1) Multimodal definitions vary, (2) Higher education curriculum, and (3) Findings of research on multimodal utilization in learning.
openaire   +3 more sources

From Wafers to Electrodes: Transferring Automatic Optical Inspection (AOI) for Multiscale Characterization of Smart Battery Manufacturing

Advanced Functional Materials, EarlyView.
Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley   +1 more source

Multimodal Multipart Learning for Action Recognition in Depth Videos

, 2015
The articulated and complex nature of human actions makes the task of action recognition difficult. One approach to handle this complexity is dividing it to the kinetics of body parts and analyzing the actions based on these partial descriptors.
Ng, Tian-Tsong, Shahroudy, Amir, Wang, Gang, Yang, Qingxiong   +3 more
core   +1 more source

From Clinic to Computation: Multiscale Bioengineering Strategies for Durable Biological Aortic Valve Replacements

Advanced Functional Materials, EarlyView.
Bioprosthetic aortic valves have revolutionized the treatment of aortic stenosis, but their durability is limited by structural valve deterioration (SVD). This review focuses on the pericardial tissue at the heart of these valves, examining how its mechanical properties and calcification drive fatigue and failure.
Gabriele Greco, Pierfrancesco Gaziano, Serena Anglese, Simone Morganti, Carlo de Vincentiis, Ferdinando Auricchio, Michele Marino, Michele Conti   +7 more
wiley   +1 more source

CentralNet: a Multilayer Approach for Multimodal Fusion

, 2018
This paper proposes a novel multimodal fusion approach, aiming to produce best possible decisions by integrating information coming from multiple media.
A Dhall, D Lahat, M Kang, N Neverova, N Neverova, PK Atrey, S Chandar, S Escalera, Y LeCun, Z Gu   +9 more
core   +1 more source