A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
A Deep Multi-Level Attentive network for Multimodal Sentiment Analysis
[article]
2020
arXiv
pre-print
Preserved Fulltext
Then we model the correlation between the image regions and semantics of the word by extracting the textual features related to the bi-attentive visual features by applying semantic attention. ...
Multimodal sentiment analysis has attracted increasing attention with broad application prospects. ...
This enhances the performance of the multimodal data for sentiment analysis. ...
arXiv:2012.08256v1
fatcat:lfx66b6dinfolnfjjngjfl6qey
Multidimensional Extra Evidence Mining for Image Sentiment Analysis
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Image sentiment analysis is conducted based on the cross-modal sentimental semantics and a general classifier. ...
sentimental semantics among diverse image features. ...
Based on the mined cross-modal sentimental semantics and a general classifier, we train a classification model for image sentiment analysis.
B. ...
doi:10.1109/access.2020.2999128
fatcat:zy2cxcydhfeolm57wcxyw3egri
GIF Video Sentiment Detection Using Semantic Sequence
2017
Mathematical Problems in Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. ...
Our experiment results on GSO-2016 (GIF Sentiment Ontology) data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art ...
According to the visual content type, recent studies can be divided into two types: image sentiment analysis and video sentiment analysis. For image sentiment analysis, You et al. ...
doi:10.1155/2017/6863174
fatcat:7pblr5zti5g4tlo5gxziwibj64
Multimodal Sentimental Analysis for Tweets
2020
International Journal of Recent Trends in Engineering and Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The proposed approach explores the correlation between the image and the text, followed by a multimodal sentiment analysis method. ...
Consequently, the conventional text-based sentiment analysis has evolved into more complicated studies of multimodal sentiment analysis. ...
By doing this, we can enhance sentiment prediction accuracy compared with only using text or image feature. ...
doi:10.23883/ijrter.conf.20200315.031.nlm7o
fatcat:y63ai7p2yfehpon2aeb7ypo4aa
Visual Sentiment Analysis on Social Media Data
2021
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Visual sentiment analysis is the way to automatically recognize positive and negative emotions from images, videos, graphics, stickers etc. ...
The proposed System will extract three views visual view, subjective text view and objective text view of social media image and will give sentiment polarity positive, negative or neutral based on hypothesis ...
., text, image, video, and audio) to perform Image Classification, Visual Sentiment Analysis [10] , Image Retrieval, and Event Classification by exploiting social media contents. ...
doi:10.32628/cseit2174101
fatcat:6kenjwhwtnez7gbjhidjmkehly
Sentiment Analysis of Chinese Paintings Based on Lightweight Convolutional Neural Network
2021
Wireless Communications and Mobile Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
To verify the effectiveness of the optimized SqueezeNet model used in the sentiment analysis of Chinese paintings, four kinds of sentiment classifications were carried out on the multitheme Chinese paintings ...
On the one hand, expand the model width to obtain more effective Chinese painting sentiment features for classification tasks, thereby improving the classification accuracy of the model. ...
Moreover, different objects in the same image may represent different sentiment classifications, such as the semantic segmentation problem in image sentiment analysis, which needs to be further studied ...
doi:10.1155/2021/6097295
fatcat:ojkhpqlk7na55heh6ch6tvbopq
Discovering Sentimental Interaction via Graph Convolutional Network for Visual Sentiment Prediction
2021
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
With the popularity of online opinion expressing, automatic sentiment analysis of images has gained considerable attention. ...
Most methods focus on effectively extracting the sentimental features of images, such as enhancing local features through saliency detection or instance segmentation tools. ...
We propose an end-to-end image sentiment analysis framework that employs GCN to extract sentimental interaction characteristics among objects. ...
doi:10.3390/app11041404
fatcat:2i4v2ce6fzg5lgsehdk24ohs3y
OutdoorSent: Sentiment Analysis of Urban Outdoor Images by Using Semantic and Deep Features
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We compare the performance of state-of-the-art ConvNet architectures, and one specifically designed for sentiment analysis. ...
For instance, particular areas of the city tend to concentrate more images of a specific class of sentiment, which are also correlated with median income, opening up opportunities in different fields. ...
This study investigates if semantic attributes (YOLO and SUN) help to enhance the performance of ConvNets for sentiment analysis in outdoor images. ...
arXiv:1906.02331v3
fatcat:6ji2wv6mffapjoceeefmou5suu
Multi-Level Context Pyramid Network for Visual Sentiment Analysis
2021
Sensors
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
sentiment analysis by combining local and global representations to improve the classification performance. ...
Finally, different levels of context features are combined to obtain the multi-cue sentimental feature for image sentiment classification. ...
[22] used the excellent model of target recognition and scene classification competition to generate objects and scene category labels as high-level semantic features for image sentiment classification ...
doi:10.3390/s21062136
pmid:33803744
fatcat:ddwzqg5yinfk3g2nqkf256bhwi
A Survey on Visual Sentiment Analysis
2020
IET Image Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2020 pre-print arXiv:2004.11639v1 fatcat:m2z7fhtjbzbdta3iwq7i2s4lt4Other Versions
Visual Sentiment Analysis aims to understand how images affect people, in terms of evoked emotions. ...
To this aim, this paper considers a structured formalization of the problem which is usually used for the analysis of text, and discusses it's suitability in the context of Visual Sentiment Analysis. ...
A number of sub-images is extracted and the sentiment analysis is performed on each sub-image obtained by exploiting methods such as multi-object detection, image segmentation, objectness extraction [ ...
doi:10.1049/iet-ipr.2019.1270
fatcat:cuhaluxac5ar5ky4rkoqmug6x4
Sentiment Interaction Distillation Network for Image Sentiment Analysis
2022
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Inspired by the observation that interaction among objects can impact the sentiment of images, we propose the Sentiment Interaction Distillation (SID) Network, which utilizes object sentimental interaction ...
It is demonstrated that the reasonable use of interaction features can improve the performance of sentiment analysis. ...
[19] achieved a higher performance by enhancing the local features in the image, which proves that local features have a promoting effect on image sentiment classification. Further, Yang et al. ...
doi:10.3390/app12073474
fatcat:gakesvsiu5arzlka2janplzvnm
Fusion of Sentiment and Asset Price Predictions for Portfolio Optimization
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
To this end, the study uses a Semantic Attention Model to predict sentiment towards an asset. ...
This paper aims to unpack and develop an enhanced understanding of the sentiment aware portfolio selection problem. ...
The analysis details that price and investor sentiment is indeed correlated. ...
arXiv:2203.05673v1
fatcat:gwuhupujxjff5ow7sy2vwocqvu
IMAGE SENTIMENTAL ANALYSIS: AN OVERVIEW
2022
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This paper introduces the area of Image Sentiment Analysis and examines the issues that it raises. ...
Sentiment analysis of such large-scale visual content can aid in better extracting user sentiments toward events or themes, such as those in image tweets, so that sentiment prediction from visual content ...
Sentiment Holder:-Almost all works on Image Sentiment Analysis ignore the sentiment holder or only evaluate the image publisher's sentiment implicitly. ...
doi:10.5281/zenodo.6507385
fatcat:t4ppdghzlvg2neswfsfovbvoai
Influencing Factors of Learning Experience in Online Large-Class Teaching ——Semantic Analysis Based on Students' Classroom Feedback Language Materials
2021
Converter
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Pearson correlation analysis on the score of text sentiment and the statistical data of questionnaire survey.The results show that the results of text semantic analysis and questionnaire survey have the ...
According to the text semantic analysis and questionnaire survey on students' learning feedback in online large classes,the NLPIR-Parser big-data semantic intelligent analysis platform is used in this ...
field, there are few researches on sentiment classification of joy, anger and sadness [21] [22] , thus learners' sentiment analysis model with the ability of realizing multi-level sentiment classification ...
doi:10.17762/converter.162
fatcat:bp44ckksmrcnxdf5lerojvv3we
A Deeper Look at Human Visual Perception of Images
2020
SN Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
A common approach is to link lower level image features with higher level properties, and train a computational model to perform classification using human-annotated ground truth. ...
Statistical analyses indicate varying importance of holistic cues, color information, semantics, and saliency on different types of attributes. ...
affected by image semantics. ...
doi:10.1007/s42979-019-0061-5
fatcat:c7if7p6765hnzpdvef35rf5y7m
« Previous
Showing results 1 — 15 out of 6,554 results