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Multimodal Misinformation Mitigation using Convolutional and Knowledge Transfer Learning Approach

Multimodal Misinformation Mitigation using Convolutional and...

引用

Sentiment analysis and Deep Learning (ICSADL), International conference on

作者： Nachiket Rathod Prabhakar Ramteke Deaprtment of Computer Science & Engineering H.V.P.M 'S College of Engineering & Technology Amravati Amravati Mahrashtra India

ISBN: (数字)9798350396157

ISBN: (纸本)9798350396164

In the era of information proliferation and digital media, the battle against the spread of misinformation has evolved into a critical challenge. This work presents an inclusive exploration of the pinnacle in misinformation mitigation, employing a multimodal method that integrates textual and visual data. Advanced techniques in knowledge transfer learning are used to develop and evaluate models for Misinformation detection based on textual content, images, and their fusion. DistilFND, a distillation of diverse models specialized in different modalities, is a focal point of proposed research. The paper involves a systematic analysis of training and testing these models on a shared dataset, enabling a comparison of their performance and the provision of insightful evaluations. Cohen's Kappa scores and ROC-AUC scores are also computed to gauge the models' efficacy. This extensive study marks a significant advance in misinformation mitigation, with knowledge transfer learning and multimodal fusion serving as pivotal elements of progress. By means of a sequence of detailed experiments and evaluation metrics, this work enhances to an improved understanding of how knowledge transfer learning, multimodal fusion, and pinnacle models can boost the correctness of Misinformation detection. The results and insights in this work aid the ongoing efforts to combat the detrimental impacts of misinformation in the digital sphere.

关键词： Training visualization Sentiment analysis Systematics Prevention and mitigation Computational modeling Network architecture

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Terrain classification through weakly-structured vehicle/terrain interaction

Terrain classification through weakly-structured vehicle/ter...

引用

IEEE International conference on Robotics and Automation (ICRA)

作者： A.C. Larson R.M. Voyles G.K. Demir Department of Computer Science University of Minnesota Minneapolis MN Department of Computer Science University of Minnesota Minneapolis MN USA Department of Electrical and Electronics Engineering Dokuz Eylul University Izmir Turkey

We present a new terrain classification technique both for effective, autonomous locomotion over natural, unknown terrains and for the qualitative analysis of terrains for exploration and mapping. Our straight-forward approach requires a single camera with little processing of visual information. Specifically, we derived a gait bounce measure from visual servoing errors that result from vehicle-terrain interactions during normal locomotion. Characteristics of the terrain, such as roughness and compliance, manifest themselves in the spatial patterns of this signal and can be extracted using pattern classification techniques. For legged robots, different limb-terrain interactions generate gait bounce signals with different information content, thus deliberate limb motions can effect higher information content (i.e. the robot is an active sensor of terrain class). Segmentation of the gait cycle based on the limb-terrain interaction isolates portions of the gait bounce signal with high information content. The decoding of, then sequencing of, this content from each cycle segment yields a robust classification of terrain type from known benchmarks. To extract this spatio-temporal pattern of the gait bounce signal, we developed a meta-classifier using discriminant analysis and hidden Markov model. We present the gait bounce derivation. We demonstrate the viability of terrain classification for legged vehicles using gait bounce with a rigorous study of more than 700 trials, obtaining 84% accuracy. We describe how terrain classification can be used for gait adaptation, particularly in relation to an efficiency metric. We also demonstrate that our technique is generally applicable to other locomotion mechanisms such as wheels and treads.

关键词： data mining Legged locomotion Robot sensing systems Remotely operated vehicles Terrain mapping Cameras visual servoing Pattern classification Signal generators Decoding

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exploration of visual Interaction Method for Metro Station Space Guidance System Based on Computer Aided Design

Exploration of Visual Interaction Method for Metro Station S...

引用

Evolutionary Algorithms and Soft Computing Techniques (EASCT), International conference on

作者： Yuwan Feng Kun Wu School Architeture & Urban Planning Shenzhen University Shenzhen Guangdong China

In recent years, the domain space interaction of subway stations based on computer-aided design has become a new trend. This article takes urban rail transit as an example to explain the importance of using computer to realize functions such as graphics and images. The system uses B/S structure to process graphic information, and stores the results in the server database for later analysis and feedback of changes in user needs. Through the simulation based on virtual sample technology, the effectiveness of the model and algorithm is verified. The visualization coefficient of the subway station domain space guidance system is between 0.7 and 0.9, the accuracy of landmarks is between 96% and 97%, the ease of use is between 84% and 89%, and the system operability is 80% above. Finally, in the computer environment, the interactive interface of the subway station domain space is designed to provide passengers with a better experience. This move means that the space interaction in the subway station has a higher technical level, and has played an important role in improving user satisfaction and convenience. In the research, it was found that the visual interaction method of the subway station spatial guidance system based on computer-aided design can be improved through the following aspects. These data may include passenger flow, train operation status, and safety information, and can be presented in the form of charts, heat maps, and animations. These research findings aim to continuously improve the spatial guidance system of subway station areas, enhance user experience and efficiency.

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data Virtual Machines: Simplifying data Sharing, exploration & Querying in Big data Environments

Data Virtual Machines: Simplifying Data Sharing, Exploration...

引用

IEEE International conference on Big data

作者： Damianos Chatziantoniou Verena Kantere Nikos Antoniou Angeliki Gantzia AUEB Greece NTUA Greece

ISBN: (纸本)9781665480468

Today’s analytics environments are characterized by a high degree of heterogeneity in terms of data systems, formats and types of analysis. Many occasions call for rapid, ad hoc, on demand construction of a data model that represents (parts of) the data infrastructure of an organization, including ML tasks. This data model is given to data scientists to play with (express reports, build ML models, explore, etc.) We present a novel graph-based conceptual model, the data Virtual Machine (DVM) representing data (persistent, transient, derived) of an organization. A DVM can be built quickly and agilely, offering schema flexibility. It is amenable to visual interfaces for schema and query management. dataframing, a frequent querying/preprocessing task in analytics applications, is usually carried out by experienced data engineers employing SQL (in the presence of a relational data warehouse) or Python/R: a procedural approach with all the known drawbacks. dataframes over DVMs are expressed declaratively - and visually, via a simple and intuitive tool. This way, non-IT experts can be involved in dataframing. In addition, query evaluation takes place within an algebraic framework with all the known benefits. I.e. a DVM enables the delegation of data engineering tasks to simpler users. We have seen analogous cases in the past, e.g. with the introduction of SQL. Finally, a DVM offers a formalism that facilitates data sharing, data portability and a single view of any entity – because a DVM’s node is an attribute and an entity at the same time. In this respect, DVMs can excellently serve as a data virtualization technique, an emerging trend in the industry. We argue that DVMs can have a significant practical impact in today’s big data environments.

关键词： visualization Query processing Organizations Big data Market research data models Virtual machining

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Visitors Vis: Interactive Mining of Suspected Medical Insurance Fraud Groups 18th

Visitors Vis: Interactive Mining of Suspected Medical Insura...

引用

18th CCF conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2023

作者： Dong, Rixin Liu, Hanlin Guo, Xu Zhou, Jiantao College of Computer Science Inner Mongolia University Hohhot China National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolia Hohhot China Engineering Research Center of Ecological Big Data Ministry of Education Hohhot China Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Hohhot China Inner Mongolia Key Laboratory of Social Computing and Data Processing Hohhot China Inner Mongolia Key Laboratory of Discipline Inspection and Supervision Big Data Hohhot China Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Hohhot China

ISBN: (纸本)9789819996360

As medical insurance continues to grow in size, the losses caused by medical insurance fraud cannot be underestimated. Current data mining and predictive techniques have been applied to analyze and explore the health insurance fraud population. However, previous studies only provide summary results and do not show the details of comparative analysis during the visit, resulting in the inability of auditors to quickly identify anomalous behavior. In this paper, we propose a visual analytics system for interactive medical insurance fraud detection to support the exploration and interpretation of different access processes. We propose a weighted MinDL to improve the accuracy of visit pattern classification in the time-series modeling process, and design a data analysis model and visual analysis view based on medical insurance fraud characteristics to reveal and explore the characteristics of medical insurance fraud groups. We collaborate with related organizations to design and implement an interactive visualization for medical insurance fraud group detection using real Medicare data and expert interviews The system is effective and practical in detecting and analyzing medical insurance fraud syndicates. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Health insurance

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CNN Based Model for Underwater Image Classification and Enhancement

CNN Based Model for Underwater Image Classification and Enha...

引用

Advances in Modern Age Technologies for Health and Engineering Science (AMATHE), International conference on

作者： Sahit Jamandlamudi Deva Priya Isravel Julia Punitha Malar Dhas Division of Data Science and Cyber Security Karunya Institute of Technology and Sciences Coimbatore India Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9798350371567

ISBN: (纸本)9798350371574

The challenge of enhancing underwater images is difficult because of several issues, including color distortion, inadequate illumination, and dispersion from suspended particles in the water. Conventional picture enhancing methods frequently find it difficult to resolve these problems. Thanks to its ability to learn intricate representations and pick up on minute features, deep learning has become a potent tool for picture improvement tasks in recent years. In this work, we suggest a novel deep learning-based method for improving underwater images. To automatically learn and improve the visual quality of underwater scenes, we use a convolutional neural network architecture that is specifically made to handle underwater photos. A sizable dataset of underwater photos is used to train the network, with an emphasis on contrast improvement and color correction. We compare our method with many state-of-the-art techniques and undertake extensive tests on a benchmark dataset to evaluate our approach. The outcomes show that our strategy performs much better than current approaches both in terms of subjective visual quality and objective criteria. Our technique improves visibility, minimizes noise, and successfully restores colors in underwater photos. By presenting a deep learning-based method that enhances the visual quality of underwater photographs, this work advances the field of underwater image processing and aids in marine research, underwater exploration, and surveillance.

关键词： Deep learning visualization Adaptation models Image color analysis Surveillance Lighting Distortion

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Multi-target Image Detection Using Pigeon-Inspired Optimization based Species Mechanism

Multi-target Image Detection Using Pigeon-Inspired Optimizat...

引用

Information Technology,Big data and Artificial Intelligence (ICIBA), International conference on IEEE International conference on

作者： Long Wang Jing Fan Xiao Wei Xincheng Cui Dongjie Wu National Computer System Engineering Research Institute of China Beijing China State-owned Changhong Machinery Factory Guilin China

ISBN: (数字)9781728152240

ISBN: (纸本)9781728152257

Multi-target detection (MTD) has a wide range of applications in target recognition, visual tracking, and other fields. The task of MTD is to find the sub-image set with the highest matching degree using the template image set from the source image. Therefore, this problem can be mapped to a multi-modal optimization problem. This paper combines the modified pigeon-inspired optimization (PIO) and species-based mechanism to perform multi-template matching tasks. To enhance the performance of our proposed method, the PIO is modified as follows: (1) the fitness of the seed is chosen as the switch signal of the map and compass operator and landmark operator; (2) in landmark operator, the halve mechanism is removed and a perturbation factor is introduced to enhance the exploration and exploitation ability. The species-based mechanism is utilized to search for multiple extreme points in parallel with multiple subpopulations. In addition, an expel mechanism is proposed to avoid the unnecessary fitness evaluation around the detected optima. Simulation results demonstrate that our proposed method performs better in detection accuracy and efficiency.

关键词： Optimization Statistics Sociology Compass Particle swarm optimization Switches Task analysis

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Automation of testing and qualification of inertial rate sensors

Automation of testing and qualification of inertial rate sen...

引用

International conference on Computer, Control and Communication

作者： Muhammad Anjum Qureshi Irfan Ahmed AERO (PVT) Limited Hasan Abdal Pakistan

ISBN: (纸本)9781424433131

A very high assurance of performance is required in case of inertial rate sensors known as gyroscopes, before finalizing the product. This assurance is provided with a high quality automated test station (ATS). The major objectives of ATS are accurate measurement of gyroscope characteristic, the comprehensive characterization and performance evaluation, while reducing testing time cycle. To assist gyro testing an ATS is created to replace manual testing processes which are very time consuming and requires expensive test equipment. The present system automates most of the processes for a fraction of the cost. The system is based on Pentium iv computer with a 16-bit data acquisition card, serial ports, rate table with integrated thermal chamber and printer. All the instruments are controlled by the host computer through RS-232. The software ldquoGyro VIEWrdquo written in visual C++ has capabilities of data acquisition, online estimation of gyroscope parameters, and run time analysis of graphs which makes it very flexible than existing softwares which support post processing. The algorithms are developed for run time processing that include mean, moving average filter, standard deviation and noise. Software allows carrying out different tests such as over thermal test, scale factor test (rotation test), misalignment test, and run-to-run test e.t.c.

关键词： Automation Automatic testing Qualifications Software testing Gyroscopes Sensor phenomena and characterization data acquisition Time measurement Test equipment Costs

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An exploration of Machine Learning Methods for Gait analysis of Potential Guide Dogs 23

An Exploration of Machine Learning Methods for Gait Analysis...

引用

Proceedings of the Tenth International conference on Animal-Computer Interaction

作者： Yifan Wu Colt Nichols Marc Foster Devon Martin James Dieffenderfer Masataka Enomoto B. Duncan X. Lascelles Jane Russenberger Gerald Brenninkmeyer Alper Bozkurt David L. Roberts Dept of Electrical and Computer Engineering North Carolina State University USA College of Veterinary Medicine North Carolina State University USA International Working Dog Registry USA Guiding Eyes for the Blind USA Dept of Computer Science North Carolina State University USA

ISBN: (纸本)9798400716560

Gait analysis is important for guide dog organizations, as ideal guide dogs have a smooth and efficient gait, where they can also easily shift between and maintain various gaits. Gait quality and natural traveling speed are two of the multiple factors important in matching a guide dog to its visually impaired handler. Gait evaluation typically includes subjective visual observation of the dog or objective assessments obtained from special-designed equipment. Guide dog organizations need a method to easily collect and analyze objective data of gait information. In this work, we explored how various machine learning models could learn and analyze gait patterns from inertial measurements data that were collected during two different data collection experiments using a wearable sensor device. We also evaluated how well each machine learning model could generalize behavior patterns from various dogs under different environments. Additionally, we compared how sensor placement locations could affect gait prediction performance by attaching the sensor device to the dog’s neck and back area respectively. The tested machine learning models were able to classify different gaits in the range of 42% to 91% in terms of accuracy, and predict various gait parameters with an error rate ranging from 14% to 29% depending on the setup. Furthermore, we also observed that using behavior data collected from the neck region contains more movement information than the back area. By performing a cross-dataset generalization test on the machine learning models, we found that even with performance drop, the models were able to learn gait-specific behavior patterns that are generalizable for different dogs. Although the results were preliminary, the proposed gait analysis exploration still showed promising potential for studying behavior patterns of candidate guide dogs.

关键词： Canine Behavior analysis Canine Gait analysis Guide Dog IMU Machine Learning

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Interpreting Distortions in Dimensionality Reduction by Superimposing Neighbourhood Graphs

Interpreting Distortions in Dimensionality Reduction by Supe...

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International conference on visualisation, VIS

作者： Benoît Colange Laurent Vuillon Sylvain Lespinats Denys Dutykh INES Univ. Grenoble Alpes Le Bourget du Lac France CNRS Univ. Grenoble Alpes Univ. Savoie Mont Blanc Chambéry France

ISBN: (纸本)9781728149424

To perform visual data exploration, many dimensionality reduction methods have been developed. These tools allow data analysts to represent multidimensional data in a 2D or 3D space, while preserving as much relevant information as possible. Yet, they cannot preserve all structures simultaneously and they induce some unavoidable distortions. Hence, many criteria have been introduced to evaluate a map's overall quality, mostly based on the preservation of neighbourhoods. Such global indicators are currently used to compare several maps, which helps to choose the most appropriate mapping method and its hyperparameters. However, those aggregated indicators tend to hide the local repartition of distortions. Thereby, they need to be supplemented by local evaluation to ensure correct interpretation of *** this paper, we describe a new method, called MING, for "Map Interpretation using Neighbourhood Graphs". It offers a graphical interpretation of pairs of map quality indicators, as well as local evaluation of the distortions. This is done by displaying on the map the nearest neighbours graphs computed in the data space and in the embedding. Shared and unshared edges exhibit reliable and unreliable neighbourhood information conveyed by the mapping. By this mean, analysts may determine whether proximity (or remoteness) of points on the map faithfully represents similarity (or dissimilarity) of original data, within the meaning of a chosen map quality criteria. We apply this approach to two pairs of widespread indicators: precision/recall and trustworthiness/continuity, chosen for their wide use in the community, which will allow an easy handling by users.

关键词： Distortion Reliability Image color analysis data visualization visualization Dimensionality reduction Three-dimensional displays

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