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Sentiment Analysis Using Deep Learning Techniques: A Review

Qurat Tul, Mubashir Ali, Amna Riaz, Amna Noureen, Muhammad Kamranz, Babar Hayat, A. Rehman
2017 International Journal of Advanced Computer Science and Applications  
of sentiment analysis such as sentiment classification, cross lingual problems, textual and visual analysis and product review analysis, etc.  ...  This Review Paper highlights latest studies regarding the implementation of deep learning models such as deep neural networks, convolutional neural networks and many more for solving different problems  ...  Jin, and J. Yang, 2015 [28] keywords Joint visual and textual model outperforms the early single fusions W. Li and H.  ... 
doi:10.14569/ijacsa.2017.080657 fatcat:us4hwclsx5ghtjo4v5vkvfkqqm

Automatic Rumor Detection on Microblogs: A Survey [article]

Juan Cao, Junbo Guo, Xirong Li, Zhiwei Jin, Han Guo, Jintao Li
2018 arXiv   pre-print
While the openness and convenience features of social media also foster many rumors online. Without verification, these rumors would reach thousands of users immediately and cause serious damages.  ...  Most rumor detection methods can be categorized in three paradigms: the hand-crafted features based classification approaches, the propagation-based approaches and the neural networks approaches.  ...  The joint representation are then fused with visual features extracted from pretrained deep VGG-19.  ... 
arXiv:1807.03505v1 fatcat:kvwukm7kofhyfd3yjlajagoxce

A Survey of Human-in-the-loop for Machine Learning [article]

Xingjiao Wu, Luwei Xiao, Yixuan Sun, Junhang Zhang, Tianlong Ma, Liang He
2022 arXiv   pre-print
Humans can provide training data for machine learning applications and directly accomplish tasks that are hard for computers in the pipeline with the help of machine-based approaches.  ...  from data processing, (2) the work of improving model performance through interventional model training, and (3) the design of the system independent human-in-the-loop.  ...  of Shanghai Municipality (19511120200).  ... 
arXiv:2108.00941v3 fatcat:kwz65h3fezbohpyixlar55v25e

MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets [article]

Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov, Md Shad Akhtar, Preslav Nakov, Tanmoy Chakraborty
2021 arXiv   pre-print
Although memes are typically humorous, recent days have witnessed an escalation of harmful memes used for trolling, cyberbullying, and abuse.  ...  To solve these tasks, we propose MOMENTA (MultimOdal framework for detecting harmful MemEs aNd Their tArgets), a novel multimodal deep neural network that uses global and local perspectives to detect harmful  ...  Then, Radford et al. (2021) proposed a competitive model, CLIP, pre-trained on 400 million image-text pairs to train a joint multimodal visual-semantic embedding layer.  ... 
arXiv:2109.05184v2 fatcat:ntmq4pv6kjdhvebjyohuikqppe

Understanding and Modeling Viewers' First Impressions with Images in Online Medical Crowdfunding Campaigns

Qingyu Guo, Siyuan Zhou, Yifeng Wu, Zhenhui Peng, Xiaojuan Ma
2022 CHI Conference on Human Factors in Computing Systems  
We compute image content, color, texture, and composition features, then analyze the correlation between these visual features and FIs.  ...  Images play a crucial role in manifesting FIs, and it is benefcial for fundraisers to understand how viewers may judge their selected images for OMCCs beforehand.  ...  ACKNOWLEDGMENTS Many thanks to the anonymous reviewers for their insightful suggestions. We thank Juanru Fang, Shixu Zhou, and Jindong Han for their valuable inputs.  ... 
doi:10.1145/3491102.3501830 fatcat:34sd4jay55g2hk6z7dgzrfoghq

Table of contents

2021 ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
University, China IVMSP-21: IMAGE & VIDEO QUALITY IVMSP-21.1: JOINT LEARNING OF IMAGE AESTHETIC QUALITY ASSESSMENT AND ................................ 1895 SEMANTIC RECOGNITION BASED ON FEATURE ENHANCEMENT  ...  , United States lxvi IVMSP-5.4: FEATURE REDUNDANCY MINING: DEEP LIGHT-WEIGHT IMAGE .........................................NON-LOCAL NETWORK FOR IMAGE .................................................  ... 
doi:10.1109/icassp39728.2021.9414617 fatcat:m5ugnnuk7nacbd6jr6gv2lsfby

The Threat of Adversarial Attacks on Machine Learning in Network Security – A Survey [article]

Olakunle Ibitoye, Rana Abou-Khamis, Ashraf Matrawy, M. Omair Shafiq
2020 arXiv   pre-print
Next, we examine various adversarial attacks against machine learning in network security and introduce two classification approaches for adversarial attacks in network security.  ...  In this survey, we first provide a taxonomy of machine learning techniques, styles, and algorithms. We then introduce a classification of machine learning in network security applications.  ...  Malicious crowdsourcing or crowd-turfing systems are used to connect users who are willing to pay, with workers who carry out malicious activities such as generation and distribution of fake news, or malicious  ... 
arXiv:1911.02621v2 fatcat:p7mgj65wavee3op6as5lufwj3q

A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks [article]

Yashar Deldjoo and Tommaso Di Noia and Felice Antonio Merra
2020 arXiv   pre-print
The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another  ...  In this survey, we provide an exhaustive literature review of 74 articles published in major RS and ML journals and conferences.  ...  [42] explore the influence of targeted adversarial attacks (i.e., FGSM [53] , and PGD [93] ) against original product images used to extract deep features in state-of-the-art visual recommender models  ... 
arXiv:2005.10322v2 fatcat:4wqcluqgnbbwpkicunn42et5te

Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey [article]

Hamed Jelodar, Yongli Wang, Chi Yuan, Xia Feng, Xiahui Jiang, Yanchao Li, Liang Zhao
2018 arXiv   pre-print
Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data, text documents.  ...  There are various methods for topic modeling, which Latent Dirichlet allocation (LDA) is one of the most popular methods in this field.  ...  Acknowledgements This article has been awarded by the National Natural Science Foundation of China (61170035, 61272420, 81674099, 61502233), the Fundamental Research Fund for the Central Universities (  ... 
arXiv:1711.04305v2 fatcat:jzsx6owjyjfo3gkbohrc2ggkzq

Adversarial Machine Learning in Text Processing: A Literature Survey

Izzat Alsmadi, Nura Aljaafari, Mahmoud Nazzal, Shadan Alhamed, Ahmad H. Sawalmeh, Conrado P. Vizcarra, Abdallah Khreishah, Muhammad Anan, Abdulelah Algosaibi, Mohammed Abdulaziz Al-Naeem, Adel Aldalbahi, Abdulaziz Al-Humam
2022 IEEE Access  
We focused on some of the evolving research areas such as: malicious versus genuine text generation metrics, defense against adversarial attacks, and text generation models and algorithms.  ...  Unlike adversarial machine learning in images, text problems and applications are heterogeneous. Thus, each problem can have its own challenges.  ...  The CNN architecture allows for learning the position and extraction of features in a variety of images. However, CNN's structure has the limitation of fixed-size inputs and fixed-size outputs.  ... 
doi:10.1109/access.2022.3146405 fatcat:emahpmjqmnbjpbhptrrtrjlja4

A Survey on Deep Learning for Human Mobility [article]

Massimiliano Luca, Gianni Barlacchi, Bruno Lepri, Luca Pappalardo
2021 arXiv   pre-print
Our survey is a guide to the leading deep learning solutions to next-location prediction, crowd flow prediction, trajectory generation, and flow generation.  ...  relevant solutions to the mobility tasks described above and the relevant challenges for the future.  ...  DeepJMT (Deep Model for Joint Mobility and Time) [28] can predict an individual's next POI as well as when they will visit it.  ... 
arXiv:2012.02825v2 fatcat:r7navzojwnaojncfsx3sbnfsze

Scanning the Issue

Azim Eskandarian
2022 IEEE transactions on intelligent transportation systems (Print)  
The authors take into account the integration of blockchain and federated learning in vehicular networks as a direction for future research.  ...  Then machine learning and blockchain techniques as novel defense mechanisms are explored to enhance the security of vehicular networks.  ...  Being omnisupervised, the efficient CNN exploits both labeled pinhole images and unlabeled panoramas.  ... 
doi:10.1109/tits.2022.3141513 fatcat:gvywr655cvgolg7rfjrqmt33b4

Technical Program

2022 2022 IEEE International Conference on Consumer Electronics (ICCE)  
Multiple sections of tone mapping curves with multiple adjustment points along explicit Bezier curve is modified for better tone mapping curve control.  ...  Simulation results show that the proposed method can adapt to both ambient light levels and the scene content to keep the creative intent in different ambient conditions.  ...  To reduce the loss of image feature during training and get more features to stabilize image generation, we use feature matching to minimize feature loss between the real and generated images for stable  ... 
doi:10.1109/icce53296.2022.9730380 fatcat:csqu3xqbczgdhpp3hbmvjpt26a

Systematic Literature Review of Security Event Correlation Methods

Igor Kotenko, Diana Gaifulina, Igor Zelichenok
2022 IEEE Access  
The research method is a systematic literature review, which includes the formulation of research questions, the choice of keywords and criteria for inclusion and exclusion.  ...  The main contribution of the review is the most complete classification and comparison of existing approaches to the security event correlation, considered not only from the point of view of the algorithm  ...  Abdullayeva [156] presents a deep autoencoder approach for automatic selection of informative features and APT classification.  ... 
doi:10.1109/access.2022.3168976 fatcat:uk3h6prqh5d73m6vrximkk2lty

Welcome message from the General Chairs

Giovanni Giambene, Boon Sain Yeo
2009 2009 International Workshop on Satellite and Space Communications  
Based on these rigorous reviews, IES 2014 accepted 106 papers for inclusion in the conference program, which represents an acceptance rate of 69%.  ...  All accepted papers will be included in the Proceeding of Adaptation, Learning and Optimization Series published by Springer-Verlag.  ...  Deep neural network exploits many layers of non-linear information for classification and pattern analysis.  ... 
doi:10.1109/iwssc.2009.5286448 fatcat:wcu4uzasizhzjmdkzyekynnqwi
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