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A Vision Enhancement Network for Image Quality Assessment

A Vision Enhancement Network for Image Quality Assessment

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2022 International conference on Culture-Oriented Science and Technology, CoST 2022

作者： Jiang, Xinyu Xu, Jiangbo Zou, Ruoyu Communication University of China Beijing China

ISBN: (数字)9781665462488

ISBN: (纸本)9781665462488

With the development and update of electronic equipment, image quality assessment has become one of the hot topics. Recently, digital image processing and convolutional neural networks (CNN) have made significant progress. However, the models based on human vision characteristics and neural feedback have poor performance in previous studies. Inspired by this, we propose a CNN-based network, vision enhancement network (VE-Net). It can filter images adaptively according to the key regions. Key regions are extracted with the incentive support method from deep information learned by CNN. The adaptive filter uses Laplacian filter and Gaussian filter. Laplacian filter adopts a linear lifting algorithm, aiming to attach the image texture to the original image. Squared earth mover's distance (EMD) loss is selected to predict the image aesthetic score distribution. VE-Net is evaluated on AVA dataset for the regression task and the classification task. Experiments show the superiority of VE-Net. © 2022 IEEE.

关键词： Textures

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Natural Language processing Approach for Classification of Archetypes Using Text on Business Environments 25

Natural Language Processing Approach for Classification of A...

引用

25th International conference on Enterprise information Systems, ICEIS 2023

作者： Mariano, Richard Vinícius Rezende de Jesus, Ana Carolina Conceição Vieira, Alessandro Garcia da Assunção Almeida de Lima, Jessica de Castro, Giulia Zanon Brandão, Wladmir Cardoso MG Belo Horizonte Brazil Sólides S.A. MG Belo Horizonte Brazil

ISBN: (纸本)9789897586484

Organizations increasingly offer resources to improve performance, minimize costs, and achieve better results. An organization is the individuals who work or provide services in it. Therefore, good organizational performance directly results from the good work of its collaborators. Identifying the archetype in the business environment can combine individuals with companies, which can improve the organizational environment and enhance the development of the individual. A person leaves traces of his behavior in what he produces, such as videos and texts. Some studies point to the possibility of identifying a behavioral profile from a textual production. In this work, we seek to identify the archetype of individuals within the business environment based on their curriculum texts. We combine the behavioral profile assessment (BPA) archetypes (Planner, Analyst, Communicator, and Executor) with 26, 636 curriculum to apply machine learning models. For this task, we used classification and regression approaches. The main algorithm used for the approaches was the SVM. The results suggest that the archetypes are better modeled using regression techniques, obtaining an MSE of 4.49 in the best case. We also provide a visual explanation example to understand the model outputs. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Support vector machines

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Towards Escaping from Language Bias and OCR Error: Semantics-Centered Text visual Question Answering

Towards Escaping from Language Bias and OCR Error: Semantics...

引用

2022 IEEE International conference on Multimedia and Expo, ICME 2022

作者： Fang, Chengyang Zeng, Gangyan Zhou, Yu Wu, Daiqing Ma, Can Hu, Dayong Wang, Weiping Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China School of Information and Communication Engineering Communication University of China Beijing China Heilongjiang Network Space Research Center Harbin150010 China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Texts in scene images convey critical information for scene understanding and reasoning. The abilities of reading and rea-soning matter for the model in the text-based visual question answering (TextVQA) process. However, current TextVQA models do not center on the text and suffer from several limitations. The model is easily dominated by language biases and optical character recognition (OCR) errors due to the ab-sence of semantic guidance in the answer prediction process. In this paper, we propose a novel Semantics-Centered Net-work (SC-Net) that consists of an instance-level contrastive semantic prediction module (ICSP) and a semantics-centered transformer module (SCT). Equipped with the two modules, the semantics-centered model can resist the language biases and the accumulated errors from OCR. Extensive experiments on TextVQA and ST-VQA datasets show the effectiveness of our model. SC- Net surpasses previous works with a notice-able margin and is more reasonable for the TextVQA task. © 2022 IEEE.

关键词： Semantics

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An Efficient Method for Secured Data communication using Chaos Encryption Algorithm

An Efficient Method for Secured Data Communication using Cha...

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2022 International conference on Innovative Computing, Intelligent communication and Smart Electrical Systems, ICSES 2022

作者： Nanammal, V. Venugopalakrishnan, J. Sathyabama Institute of Science and Technology Dept of ECE Chennai India Madha Engineering College Chennai India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

To prevent the information theft from attackers there is a need of mechanism to secure the data. In order to successfully deal with image information theft, it must look for a improved encryption algorithm. Past few decades several algorithms were developed, due to the preponderation of chaos technology, when the image is encrypted with chaos technology, the ciphertext presents an arbitrariness, which makes the possible action of deciphering greatly abbreviated. In this paper, another methodology of Chaos encryption has been proposed. This methodology shows irregular conduct that can be used for secure encryption and proficient information transmission. The unbending nature of this methodology can be investigated and observed by execution factors for example, testing towards numerous image processing attacks, measurement of Peak signal to noise ratio, Mean square error values. Image with various scaling factors provide low MSE rate and high PSNR by utilizing this chaotic strategy. This strategy is demonstrated to be extremely successful compared to the other existing systems. The proposed methodology is adaptable and highly effective because of its affectability to secret key and appropriate for different applications such as military, legal and medical systems, overall visual check by offering simultaneous security functions. © 2022 IEEE.

关键词： Cryptography

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Encoder Optimization information SEI Message for Identifying Optimization Objectives and Methods

Encoder Optimization Information SEI Message for Identifying...

引用

IEEE visual communications and Image processing (VCIP)

作者： Chul Keun Kim Hendry Tan Jaehyun Lim Seung Hwan Kim LG Electronics Seoul Korea LG Electronics San Diego USA

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

This paper presents the Encoder Optimization information (EOI) SEI message, which was recently included in the Versatile Supplemental Enhancement information (VSEI) version 4 draft standard and is ongoing work within the Joint Video Experts Team (JVET) group. As the use of video content diversifies, there is an increasing need to apply preprocessing/task-driven encoding to optimize the coded bitstream for its intended use. Such optimization may be targeted for human viewing, machine analysis tasks, or both. Additionally, for better utilization of the coded bitstream, tailoring optimization for intended uses allows for the exclusion of unnecessary information, potentially reducing bitrate and enhancing compression efficiency. The EOI SEI message is designed to contain information about the optimization applied during the video encoding process and the intended usages of such optimization. Decoders may utilize the information provided by the EOI SEI message to effectively use video content that best fits their specific requirements and conditions.

关键词： Image coding visual communication Bit rate Decoding Object recognition Optimization Standards Binary sequences

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A Novel Multi-modal Feature Extraction System for News Video

A Novel Multi-modal Feature Extraction System for News Video

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2023 International conference on Automation Control, Algorithm, and Intelligent Bionics, ACAIB 2023

作者： Xue, Ruiqi Communication University of China Beijing China

ISBN: (纸本)9781510667662

Advancements in artificial intelligence technology are leading to significant transformations in the generation of news. This article presents the News Video Style Feature Automatic Extraction System (NVFAE), which leverages state-of-the-art open-source technologies such as Automatic Speech Recognition, Optical Character Recognition, and Natural Language processing. The NVFAE extracts news video style features from multiple modalities: textual features, visual features, and delivery features. The system uses automated annotation to extract five distinct style features from news videos: high-frequency words, overall tense, video color tone, main character, and video length. 38 BBC videos about the topic of "Turkey earthquake" from the YouTube platform are chosen for testing NVFAE, whose five features can be all successfully extracted. Experimental results show that the system proposed in this paper can provide a digital and structured way to explore the narrative characteristics of news videos, only with a mouse click and style features of news videos can be obtained in batches. NVFAE is aimed to overcome the difficulties of manual annotation for video news, as well as supply news workers with valuable references to study the news styles and content planning. © 2023 SPIE.

关键词： Feature extraction

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Design of Crawler and visual Interactive Interface Based on Scrapy Framework

Design of Crawler and Visual Interactive Interface Based on ...

引用

Electronic Technology, communication and information (ICETCI), IEEE International conference on

作者： Lili Gao Qi Meng Department of Information Science and Engineering Shandong Agriculture and Engineering University Jinan China

Nowadays, when studying and analyzing problems, the previous conventional analysis methods are obviously difficult to meet our needs in such a huge data scale environment. At the same time, the emergence of web crawlers solves the problem of data acquisition under big data. This paper completes a series of tasks such as data acquisition, download and storage in the designated website by studying the scrapy framework. At the same time, through the research of pyecharts library, JSON library and other visualization related technologies, we can realize the visual processing and display of the crawling data of the scrapy framework, so as to realize the more intuitive analysis of the data.

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visual-Aware Text-to-Speech*

Visual-Aware Text-to-Speech*

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Mohan Zhou Yalong Bai Wei Zhang Ting Yao Tiejun Zhao Tao Mei Harbin Institute of Technology Harbin China JD Explore Academy Beijing China

Dynamically synthesizing talking speech that actively responds to a listening head is critical during the face-to-face interaction. For example, the speaker could take advantage of the listener’s facial expression to adjust the tones, stressed syllables, or pauses. In this work, we present a new visual-aware text-to-speech (VA-TTS) task to synthesize speech conditioned on both textual inputs and sequential visual feedback (e.g., nod, smile) of the listener in face-to-face communication. Different from traditional text-to-speech, VA-TTS highlights the impact of visual modality. On this newly-minted task, we devise a baseline model to fuse phoneme linguistic information and listener visual signals for speech synthesis. Extensive experiments on multimodal conversation dataset ViCo-X verify our proposal for generating more natural audio with scenario-appropriate rhythm and prosody.

关键词： visualization Statistical analysis Synthesizers Oral communication Signal processing Linguistics Rhythm

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Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval 24

Focus, Distinguish, and Prompt: Unleashing CLIP for Efficien...

引用

32nd ACM International conference on Multimedia, MM 2024

作者： Zeng, Gangyan Zhang, Yuan Wei, Jin Yang, Dongbao Zhang, Peng Gao, Yiwen Qin, Xugong Zhou, Yu School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China Lenovo Research Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China Laboratory for Advanced Computing and Intelligence Engineering Wuxi China TMCC College of Computer Science Nankai University Tianjin China

ISBN: (纸本)9798400706868

Scene text retrieval aims to find all images containing the query text from an image gallery. Current efforts tend to adopt an Optical Character Recognition (OCR) pipeline, which requires complicated text detection and/or recognition processes, resulting in inefficient and inflexible retrieval. Different from them, in this work we propose to explore the intrinsic potential of Contrastive Language-Image Pre-training (CLIP) for OCR-free scene text retrieval. Through empirical analysis, we observe that the main challenges of CLIP as a text retriever are: 1) limited text perceptual scale, and 2) entangled visual-semantic concepts. To this end, a novel model termed FDP (Focus, Distinguish, and Prompt) is developed. FDP first focuses on scene text via shifting the attention to the text area and probing the hidden text knowledge, and then divides the query text into content word and function word for processing, in which a semantic-aware prompting scheme and a distracted queries assistance module are utilized. Extensive experiments show that FDP significantly enhances the inference speed while achieving better or competitive retrieval accuracy compared to existing methods. Notably, on the IIIT-STR benchmark, FDP surpasses the state-of-the-art model by 4.37% with a 4 times faster speed. Furthermore, additional experiments under phrase-level and attribute-aware scene text retrieval settings validate FDP's particular advantages in handling diverse forms of query text. The source code will be available at https://***/Gyann-z/FDP. © 2024 ACM.

关键词： Semantics

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Efficient Architecture for Multi-Robot visual SLAM Systems

Efficient Architecture for Multi-Robot Visual SLAM Systems

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International Carpathian Control conference (ICCC)

作者： Omar M. Salih József Vásárhelyi Institute of Automation and Info-Communication University of Miskolc Miskolc Hungary Technical College of Kirkuk Northern Technical University Mosul Iraq

ISBN: (数字)9798331501273

ISBN: (纸本)9798331501280

visual Simultaneous Localization and Mapping (VS-LAM) is a crucial algorithm used in mobile robots to determine their position relative to the encirclement environment. In multi-robot architectures, mobile robots communicate with a base station or a centralized edge device. However, the computational complexity nature of the VSLAM algorithm, due to the processing of massive visual information for tracking and mapping, poses challenges for deploying the algorithm entirely on the mobile robot. To address these limitations, this paper introduces an efficient architecture that partitions the V-SLAM framework between mobile robots and a centralized edge. This approach complies with resource limitations and optimizes energy consumption while minimizing the robot’s size and weight. In addition, the paper proposes a communication module comprising an encoding and decoding framework to obtain effective data communication between the mobile robots and the edge device. The performance of the proposed system is evaluated and compared with a corresponding architecture that employs the baseline JPEG technique in terms of trajectory accuracy, data quality, and execution time.

关键词： Performance evaluation visualization Simultaneous localization and mapping Data integrity System performance Transform coding Computer architecture Partitioning algorithms Trajectory Mobile robots

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