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检索条件"任意字段=IEEE Information Visualization Conference/IEEE Visualization Conference"

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Data visualization and Analytics for Price Elasticity on Commodities Using Machine Learning Techniques

Data Visualization and Analytics for Price Elasticity on Com...

引用

2023 International conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Nagaraj, P. Charan Vivek Raj, R. Shigivahan, A. Kalasalingam Academy of Research and Education Anand Nagar Department of Computer Science and Engineering Tamil Nadu Krishnankoil India

ISBN: (纸本)9798350348910

Nowadays, many commodities are being sold across restaurants. Many commodities would earn profit to the seller on the other hand some may provide loss. Predicting the price of a commodity leads to success in terms of sales. Machine learning practices are used to forecast the price elasticities of various commodities. The price elasticity model with the amalgamation of Ordinary least squares will lead to perceiving the seller's demand. This process leads to an increased profit for Quick Service Restaurants. The seller can identify where the raw materials can be purchased very cheaply according to that price can be also increased or decreased on the facets like commodity exigency and relativism with the antiquated price. © 2023 ieee.

关键词： Profitability

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Learning to Answer Questions in Dynamic Audio-Visual Scenarios

Learning to Answer Questions in Dynamic Audio-Visual Scenari...

引用

ieee/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Li, Guangyao Wei, Yake Tian, Yapeng Xu, Chenliang Wen, Ji-Rong Hu, Di Renmin Univ China Gaoling Sch Artificial Intelligence Beijing Peoples R China Beijing Key Lab Big Data Management & Anal Method Beijing Peoples R China Univ Rochester Dept Comp Sci Rochester NY 14627 USA

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

In this paper, we focus on the Audio-Visual Question Answering (AVQA) task, which aims to answer questions regarding different visual objects, sounds, and their associations in videos. The problem requires comprehensive multimodal understanding and spatio-temporal reasoning over audio-visual scenes. To benchmark this task and facilitate our study, we introduce a large-scale MUSIC-AVQA dataset, which contains more than 45K question answer pairs covering 33 different question templates spanning over different modalities and question types. We develop several baselines and introduce a spatio-temporal grounded audio-visual network for the AVQA problem. Our results demonstrate that AVQA benefits from multisensory perception and our model outperforms recent A-, V-, and AVQA approaches. We believe that our built dataset has the potential to serve as testbed for evaluating and promoting progress in audio-visual scene understanding and spatio-temporal reasoning. Code and dataset: http://***/MUSIC-AVQA/

关键词： visualization Computer vision Image analysis Codes Computational modeling Cognition Question answering (information retrieval)

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Fuzzy Optimization in Electrical Tomography Imaging Based on Expectation-Maximization Algorithm

Fuzzy Optimization in Electrical Tomography Imaging Based on...

引用

ieee Instrumentation and Measurement Technology conference

作者： Honghao Qu Shihong Yue Fanpeng Dong school of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Electrical Tomography (ET) is an advanced visualization technique with low-cost, non-invasiveness, nonpolluting, and fast-response advantages. However, inherent illposed problems and soft-field effects in the ET reconstruction process cause uncertainty in boundary measurements, thereby decreasing the quality of ET reconstruction. To solve this problem, this study employs Gaussian-type fuzzy membership functions to represent measurement uncertainty. The study constructs the objective function for ET reconstruction and performs fuzzy optimization using the Expectation-Maximization (EM) algorithm, aiming to enhance the accuracy and stability of ET reconstruction. Experimental findings affirm the effectiveness of the proposed approach in improving the ET reconstruction quality, offering a novel and valuable tool for ET reconstruction.

关键词： visualization Accuracy Uncertainty Measurement uncertainty Tomography Stability analysis Noise measurement

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Performance Analysis of Feature Extraction Methods towards Underwater vSLAM 17

Performance Analysis of Feature Extraction Methods towards U...

引用

ieee 17th International conference on Control and Automation (ICCA)

作者： Wu, Di Wang, Yue Hou, Dongdong Hao, Lichao Zhang, Liukun Wang, Di Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China Harbin Engn Univ Qingdao Innovat & Dev Ctr Qingdao 266404 Peoples R China Res Inst CSSC Zhengzhou 450015 Peoples R China Henan Key Lab Underwater Intelligent Equipment Zhengzhou 450015 Peoples R China

ISBN: (数字)9781665495721

ISBN: (纸本)9781665495721

In recent years, the rapid development of Visual Simultaneous Localization and Mapping (vSLAM) technology has provided improvements for robot localization. However, for autonomous underwater vehicles, feature extraction methods in underwater environments have not been studied much due to the specificity of their application scenarios. For this purpose, this paper evaluates and analyzes the performance of feature detecting and matching in underwater environments by using well-known interest points detectors and descriptors in vSLAM. The performance of different well-known interest points detectors and descriptors is compared and analyzed by simulation experiments using four sets of underwater image data and combining histogram equalization-based and deep learning-based image enhancement algorithms. The experimental results have verified the effectiveness of the image enhancement algorithm and feature extraction methods in underwater environments, and the quantitative comparison concludes that ORB algorithm has an advantage in underwater environments.

关键词： visualization Histograms Autonomous underwater vehicles Simultaneous localization and mapping Detectors Feature extraction Robot localization

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CoolTeD: A Web-based Collaborative Labeling Tool for the Textual Dataset 29

CoolTeD: A Web-based Collaborative Labeling Tool for the Tex...

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29th ieee International conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Wang, Chong Jiang, Jingwen Daneva, Maya Van Sinderen, Marten Wuhan Univ Sch Comp Sci Wuhan Peoples R China Univ Twente Fac Elect Engn Math & Comp Sci Enschede Netherlands

ISBN: (纸本)9781665437868

High-quality labeled textual data are vital for automatic mining and analysis of massive textual data produced by software systems. Several tools have been designed to facilitate manual labeling of textual data on different levels of granularity. However, these tools neither aim to provide statistics and analysis of labeled textual data, nor support collaboration among the coders to reduce the time cost in manual labeling and enhance the quality of labeling results. In this paper, we developed a Web-based labeling tool named CoolTeD (available at http://***) for collaborative labeling of the textual datasets. Specifically, CoolTeD can be used: (1) to label textual data from the perspective of requirements types based on ISO 25010, (2) to review the labeling results with different confidence levels and contradictory labels, (3) to automatically calculate Cohen's Kappa coefficient of multiple coders, and (4) to visualize the labeling results. The tool demo is available at https://***/xVkrB_Cs1J8

关键词： Data Labeling Collaborative Labeling Textual Data Data visualization Requirements Engineering

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Construction of visualization Model of Maternal Health Care Based on Domain Ontology 3

Construction of Visualization Model of Maternal Health Care ...

引用

3rd ieee International conference on Civil Aviation Safety and information Technology, ICCASIT 2021

作者： Zhang, Ming'e Zhang, Hui Wuhan Railway Vocational College of Technology Wuhan China Wuhan Institute of Shipbuilding Technology Wuhan China

ISBN: (纸本)9781665425186

In order to effectively analyze and utilize a large number of maternal health care diagnosis and treatment guidelines, electronic medical records and clinical data, and promote the sharing and reuse of knowledge and experience in the field of maternal health care, the project uses ontology technology to carry out semi-automatic ontology construction through analysis and reference seven steps and knowledge extraction technology, The ontology knowledge base model of pregnancy and childbirth domain is constructed. In order to further show the domain ontology of pregnancy and childbirth, through the visual analysis of the domain ontology of pregnancy and childbirth, using data visualization technology and domain oriented strategy, this paper constructs the domain ontology visualization model of pregnancy and childbirth. © 2021 ieee

关键词： Health care

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Vision-aided Dynamic Quadrupedal Locomotion on Discrete Terrain using Motion Libraries 39

Vision-aided Dynamic Quadrupedal Locomotion on Discrete Terr...

引用

ieee International conference on Robotics and Automation (ICRA)

作者： Agrawal, Ayush Chen, Shuxiao Rai, Akshara Sreenath, Koushil Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA Meta AI Detroit MI USA

ISBN: (纸本)9781728196817

In this paper, we present a framework rooted in control and planning that enables quadrupedal robots to traverse challenging terrains with discrete footholds using visual feedback. Navigating discrete terrain is challenging for quadrupeds because the motion of the robot can be aperiodic, highly dynamic, and blind for the hind legs of the robot. Additionally, the robot needs to reason over both the feasible footholds as well as the base velocity in order to speed up or slow down at different parts of the discrete terrain. To address these challenges, we build an offline library of periodic gaits which span two trotting steps, and switch between different motion primitives to achieve aperiodic motions of different step lengths on a quadrupedal robot. The motion library is used to provide targets to a geometric model predictive controller which outputs the contact forces at the stance feet. To incorporate visual feedback, we use terrain mapping tools and a forward facing depth camera to build a local height map of the terrain around the robot, and extract feasible foothold locations around both the front and hind legs of the robot. Our experiments show a small scale quadruped robot navigating multiple unknown, challenging and discrete terrains in the real world.

关键词： Legged locomotion visualization Navigation Dynamics Terrain mapping Turning Libraries

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Improving Visual Grounding with Visual-Linguistic Verification and Iterative Reasoning

Improving Visual Grounding with Visual-Linguistic Verificati...

引用

ieee/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yang, Li Xu, Yan Yuan, Chunfeng Liu, Wei Li, Bing Hu, Weiming Chinese Acad Sci Inst Automat NLPR Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Shanghai Peoples R China

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

Visual grounding is a task to locate the target indicated by a natural language expression. Existing methods extend the generic object detection framework to this problem. They base the visual grounding on the features from pre-generated proposals or anchors, and fuse these features with the text embeddings to locate the target mentioned by the text. However, modeling the visual features from these predefined locations may fail to fully exploit the visual context and attribute information in the text query, which limits their performance. In this paper, we propose a transformer-based framework for accurate visual grounding by establishing text-conditioned discriminative features and performing multi-stage cross-modal reasoning. Specifically, we develop a visual-linguistic verification module to focus the visual features on regions relevant to the textual descriptions while suppressing the unrelated areas. A language-guided feature encoder is also devised to aggregate the visual contexts of the target object to improve the object's distinctiveness. To retrieve the target from the encoded visual features, we further propose a multi-stage cross-modal decoder to iteratively speculate on the correlations between the image and text for accurate target localization. Extensive experiments on five widely used datasets validate the efficacy of our proposed components and demonstrate state-of-the-art performance.

关键词： Location awareness visualization Grounding Natural languages Object detection Transformers Cognition

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Design and Prototyping of Soft Finger AI-Enabled Hand (SofIA)

Design and Prototyping of Soft Finger AI-Enabled Hand (SofIA...

引用

ieee/ASME International conference on Advanced Intelligent Mechatronics (AIM)

作者： Stuhne, Dario Tabak, Jelena Polic, Marsela Orsag, Matko Univ Zagreb LARICS Lab Robot & Intelligent Control Syst Fac Elect Engn & Comp Zagreb 10000 Croatia

ISBN: (数字)9781665413084

ISBN: (纸本)9781665413084

This paper presents the design and prototype of soft-fingered AI-enabled hand (SofIA) based on the Fin-Ray (R) effect. The study proposes a material and method for fabricating soft Fin-Ray fingers by molding them entirely from urethane rubber. SofIA is equipped with a depth camera that provides visual feedback on the state of the fingers, which will be used in the development of a versatile sensing system based on deep learning. Flexible side supports were added to further improve the mechanical performance of the fingers. Using SofIA, a series of experiments were conducted with the original and modified FinRay finger structures to test and validate the desired behaviour of the gripper. It was found that the hand is capable of manipulating objects ranging from 10 mm to 90 mm in diameter, objects up to 90 mm x 90 mm in length and width, and objects with a maximum mass of 400 g in a position parallel to the ground regardless of the object material.

关键词： Deep learning visualization Mechatronics Prototypes Cameras Distance measurement Sensors

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A Digital Twin-Driven Hybrid Estimate Method for Health Status of Train Braking System 25

A Digital Twin-Driven Hybrid Estimate Method for Health Stat...

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25th ieee International conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Peng, Jun Zhao, Qin Gao, Dianzhu Yang, Yingze Zhou, Feng Rong, Jieqi Fan, Yunsheng Liu, Bowen Jiang, Fu Zhang, Xiaoyong Central South University School of Computer Science and Engineering Changsha China Central South University School of Automation Changsha China Changsha University of Science and Technology School of Electrical and Information Engineering Changsha China Hunan Engineering Laboratory of Rail Vehicles Braking Technology Changsha China

ISBN: (纸本)9781665405270

The braking system is the key part of trains, and its full life-cycle of health status is essential to ensure the safety of trains. How to accurately assess real-time health status throughout the full life-cycle of the train braking system is a challenge. In this paper, a digital twin-driven hybrid estimate method for health status of the braking system is proposed. Firstly, an equivalent model of the braking system is built in the digital twin platform. Then, a hybrid method of fusing model and data is proposed to assess the health status. Finally, a cloud digital twin experimental platform for health status assessment of the braking system is built, and the health status is shown by visualization framework. The experiments verify the effectiveness and practicality of the proposed scheme. © 2022 ieee.

关键词： Life cycle

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