Text and Image: Representation in Grimmelshausen's Continuatio

1991 ◽  
Vol 64 (2) ◽  
pp. 138 ◽  
Author(s):  
Richard E. Schade
Keyword(s):  
Image Representation ◽  
Text And Image

scholarly journals Multilevel Attention Residual Neural Network for Multimodal Online Social Network Rumor Detection

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhuang Wang ◽  
Jie Sui
Keyword(s):  
Neural Network ◽  
Social Network ◽  
State Of The Art ◽  
Online Social Network ◽  
Image Representation ◽  
Rapid Rise ◽  
Text And Image ◽  
Detection Model ◽  
Fused Image ◽  
Rumor Detection

In recent years, with the rapid rise of social networks, such as Weibo and Twitter, multimodal social network rumors have also spread. Unlike traditional unimodal rumor detection, the main difficulty of multimodal rumor detection is in avoiding the generation of noise information while using the complementarity of different modal features. In this article, we propose a multimodal online social network rumor detection model based on the multilevel attention residual neural network (MARN). First, the features of text and image are extracted by Bert and ResNet-18, respectively, and the cross-attention residual mechanism is used to enhance the representation of images with a text vector. Second, the enhanced image vector and text vector are concatenated and fused by the self-attention residual mechanism. Finally, the fused image–text vectors are classified into two categories. Among them, the attention mechanism can effectively enhance the image representation and further improve the fusion effect between the image and the text, while the residual mechanism retains the unique attributes of each original modal feature while using different modal features. To assess the performance of the MARN model, we conduct experiments on the Weibo dataset, and the results show that the MARN model outperforms the state-of-the-art models in terms of accuracy and F1 value.

Indian Horse

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Casey Shea Pollon
Keyword(s):  
University Students ◽  
Key Words ◽  
Point Of View ◽  
Main Element ◽  
Text And Image ◽  
Design Studies ◽  
Visual Form ◽  
Diploma Program

Type as Image: Eliciting Emotions is a project of VCDE233 Typography II (Constanza Pacher) and VCDI223 Design and Pre-Press Production (Jess Dupuis), both courses in the Design Studies Diploma Program at MacEwan University. Students were asked to capture the essence of the book Indian Horse, by Richard Wagamese, and translate it into a three-poster series using typography as the main element. Under the premise that the visual form is dictated by the content, students were encouraged to analyze plot, characters, point of view, imagery, tone, themes and symbolism to extract key words, sentences and passages as the basis for their designs. Students were asked to challenge literal interpretations by exploring the use of expressive typography and text and image relationships.

Convolutional Dictionary Pair Learning Network for Image Representation Learning.pdf

2019 ◽  
Author(s):  
Zhao Zhang ◽  
Yulin Sun ◽  
Yang Wang ◽  
Zhengjun Zha ◽  
Shuicheng Yan ◽  
...  
Keyword(s):  
Image Representation ◽  
Learning Network

10 pages, 6 figures

Image Representation Using Bag-of-phrases

2012 ◽  
Vol 38 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Lin-Bo ZHANG ◽  
Chun-Heng WANG ◽  
Bai-Hua XIAO ◽  
Yun-Xue SHAO
Keyword(s):  
Image Representation

Image Reconstruction for Compressed Sensing Based on the Combined Sparse Image Representation

2010 ◽  
Vol 36 (3) ◽  
pp. 385-391 ◽  
Author(s):  
Qiu-Sheng LIAN ◽  
Shu-Zhen CHEN
Keyword(s):  
Image Reconstruction ◽  
Compressed Sensing ◽  
Image Representation

Text and Image in Two Fifteenth-Century Dutch Psalters from Delft

1990 ◽  
Vol 64 (1) ◽  
pp. 41-52
Author(s):  
J.H. MARROW
Keyword(s):  
Fifteenth Century ◽  
Text And Image
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