Multimodal machine learning: A survey and taxonomy
Our experience of the world is multimodal-we see objects, hear sounds, feel texture, smell
odors, and taste flavors. Modality refers to the way in which something happens or is …
odors, and taste flavors. Modality refers to the way in which something happens or is …
An overview on restricted Boltzmann machines
Abstract The Restricted Boltzmann Machine (RBM) has aroused wide interest in machine
learning fields during the past decade. This review aims to report the recent developments in …
learning fields during the past decade. This review aims to report the recent developments in …
Deep multimodal representation learning: A survey
W Guo, J Wang, S Wang - Ieee Access, 2019 - ieeexplore.ieee.org
Multimodal representation learning, which aims to narrow the heterogeneity gap among
different modalities, plays an indispensable role in the utilization of ubiquitous multimodal …
different modalities, plays an indispensable role in the utilization of ubiquitous multimodal …
Comparative analysis on cross-modal information retrieval: A review
Human beings experience life through a spectrum of modes such as vision, taste, hearing,
smell, and touch. These multiple modes are integrated for information processing in our …
smell, and touch. These multiple modes are integrated for information processing in our …
Deeply supervised subspace learning for cross-modal material perception of known and unknown objects
In order to help robots understand and perceive an object's properties during noncontact
robot-object interaction, this article proposes a deeply supervised subspace learning …
robot-object interaction, this article proposes a deeply supervised subspace learning …
Generalized deep transfer networks for knowledge propagation in heterogeneous domains
In recent years, deep neural networks have been successfully applied to model visual
concepts and have achieved competitive performance on many tasks. Despite their …
concepts and have achieved competitive performance on many tasks. Despite their …
Forming a new small sample deep learning model to predict total organic carbon content by combining unsupervised learning with semisupervised learning
The total organic carbon (TOC) content is a parameter that is directly used to evaluate the
hydrocarbon generation capacity of a reservoir. For a reservoir, accurately calculating TOC …
hydrocarbon generation capacity of a reservoir. For a reservoir, accurately calculating TOC …
Exploration of Chinese sign language recognition using wearable sensors based on deep belief net
Y Yu, X Chen, S Cao, X Zhang… - IEEE journal of …, 2019 - ieeexplore.ieee.org
In this paper, deep belief net (DBN) was applied into the field of wearable-sensor based
Chinese sign language (CSL) recognition. Eight subjects were involved in the study, and all …
Chinese sign language (CSL) recognition. Eight subjects were involved in the study, and all …
A survey on multi-modal social event detection
H Zhou, H Yin, H Zheng, Y Li - Knowledge-Based Systems, 2020 - Elsevier
Due to the prevalence of social media sites, users are allowed to conveniently share their
ideas and activities anytime and anywhere. Therefore, these sites hold substantial real …
ideas and activities anytime and anywhere. Therefore, these sites hold substantial real …
Exploring global and local linguistic representations for text-to-image synthesis
The task of text-to-image synthesis is to generate photographic images conditioned on given
textual descriptions. This challenging task has recently attracted considerable attention from …
textual descriptions. This challenging task has recently attracted considerable attention from …