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检索条件"丛书名=Advances in Intelligent Systems and Computing"

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Indoor-Outdoor Scene Classification with Residual Convolutional Neural Network 3rd

Indoor-Outdoor Scene Classification with Residual Convolutio...

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3rd International Conference on Computer Vision and Image Processing (CVIP)

作者： Kumari, Seema Jha, Ranjeet Ranjan Bhavsar, Arnav Nigam, Aditya IIT Mandi MAS Lab Sch Comp & Elect Engn Kamand India

ISBN: (纸本)9789813292918;9789813292901

In this paper, we demonstrate the effectiveness of a customized ResNet to address the problem of indoor-outdoor scene classification both for color images as well as depth images. Such an approach can serve as an initial step in a scene classification/retrieval pipeline or a single-image depth estimation task. The classification framework is developed based on Residual Convolutional Neural Network (ResNet-18) to classify any random scene as indoor or outdoor. We also demonstrate the invariance of the classification performance with respect to different weather conditions of outdoor scenes (which one can commonly encounter). The performance of our classification strategy is analyzed on different varieties of publicly available datasets of indoor and outdoor scenes that also have corresponding depth maps. The suggested approach achieves almost an ideal performance in many scenarios, for both color and depth images, across datasets. We also show positive comparisons with other state-of-the-art methods.

关键词： Scene classification RCNN Scene analysis Depth information Image retrieval

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SOM-Based Anomaly Detection and Localization for Space Subsystems 13th

SOM-Based Anomaly Detection and Localization for Space Subsy...

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13th International Workshop on Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (WSOM)

作者： Rosengarten, Maia Ramachandran, Sowmya Stottler Henke Associates Inc San Mateo CA 94402 USA

ISBN: (纸本)9783030196417;9783030196424

The aim of this paper is to contribute to machine-learning technology that expands real-time and offline Integrated System Health Management capabilities for future deep-space exploration efforts. To this end, we have developed Anomaly Detection via Topological feature-Map (ADTM), which leverages a Self-Organizing Map (SOM)-based architecture to produce high-resolution clusters of nominal system behavior. What distinguishes ADTM from more common clustering techniques (e.g. k-means) is that it maps high-dimensional input vectors to a 2D grid while preserving the topology of the original dataset. The result is a 'semantic map' that serves as a powerful tool for uncovering latent relationships between features of the incoming data points. We successfully modeled and analyzed datasets from a NASA Ames Research Center Graywater Recycling System which documents a real hardware system fault. Our results show that ADTM effectively detects both known and unknown anomalies and identifies the correlated measurands from models trained using just nominal data.

关键词： Self-Organizing Map Anomaly detection and localization Integrated System Health Management

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Managing Tasks in Confidence Based Learning Using K-ary Tree 2nd

Managing Tasks in Confidence Based Learning Using K-ary Tree

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22nd International Conference on Interactive Collaborative Learning (ICL) / 48th IGIP International Conference on Engineering Pedagogy - Impact of the 4th Industrial Revolution on Engineering Education

作者： Chatterjee, Rajeev Kar, Sadhu Prasad Mandal, Jyotsna Kumar Natl Inst Tech Teachers Training & Res Block FCSect 3 Kolkata 700106 India Univ Kalyani Kalyani W Bengal India

ISBN: (纸本)9783030402716;9783030402709

Confidence Based Learning (CBL) is a newer method of teaching and learning system that not only identify the knowledge of a typical learner but also takes care of the confidence level in the knowledge for its practical use in professional world. Unlike, other e-learning systems, the CBL first assesses a learner and identifies the knowledge level and skill gaps and the limitation of confidence level. The authors in this manuscript propose a k-ary tree structure to represent tasks and Atomic Competencies (ACs) related to an Instructional Objective (IO). Structure of Learning Object (LO) and 2-dimensional assessment technique for CBL is available, but it lacks in proper trace of progressions. A mining technique using LRS for improvised identification of limitations of a learner is also suggested in the research. In this research proposal, the authors explain how a k-ary tree may be used for implementation of the tasks and ACs so that proper diagnosis can be performed, and a customized learning content can be provided. The authors proposed an optimization technique using Huffman/Dynamic Huffman Tree to quantify the progression towards mastery. The research article emphasizes of the progressive model towards the learners' mastery. This not only provide a learning map to the learner but also help the course designer to trace the respective learners' performance.

关键词： e-Learning Technology Enabled Learning CBL CBA

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Teaching Mobile Robotics Using the Autonomous Driving Simulator of the Portuguese Robotics Open 4th

Teaching Mobile Robotics Using the Autonomous Driving Simula...

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4th Iberian Robotics Conference (Robot) - advances in Robotics

作者： Costa, Valter Cebola, Peter Tavares, Pedro Morais, Vitor Sousa, Armando INEGI Inst Sci & Innovat Mech & Ind Engn Porto Portugal Univ Porto FEUP Fac Engn Porto Portugal INESC TEC INESC Technol & Sci INESC Porto Porto Portugal Univ Porto Dept Elect & Comp Engn Fac Engn Porto Portugal

ISBN: (纸本)9783030359904;9783030359898

Teaching mobile robotics adequately is a complex task. Within the strategies found in the literature, the one used in this work includes the use of a simulator. This simulator represents the Autonomous Driving Competition of the Portuguese Robotics Open. Currently, the simulator supports two different robots and all challenges of the autonomous driving competition. This simulator was used at a Robotics course of the Integrated Master Degree in Informatics and computing Engineering at the Faculty of Engineering of the University of Porto. In order to study the influence of the simulator in the college students learning process, a survey was conducted. The results and its corresponding analysis indicate that the simulator is suited to teach some of the mobile robotics challenges crossing several fields of study, including image processing, computer vision and control.

关键词： Educational robotics Autonomous driving simulator Portuguese Robotics Open Gazebo ROS Mobile robotics Autonomous Driving Competition

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Application and Practice of Deep Learning Platform in Automobile Field

Application and Practice of Deep Learning Platform in Automo...

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International Conference on Cyber Security Intelligence and Analytics (CSIA)

作者： Wang, Yingzi Fang, Xiangyi Hou, Jue China Automot Technol & Res Ctr Co Ltd Tianjin 300300 Peoples R China

ISBN: (纸本)9783030152352;9783030152345

Starting from the development trend of the automotive field, this paper describes the development of the automotive field at home and abroad, and mainly studies the application examples of the deep learning platform in the automotive field, and explores the convenience and advantages brought by the deep learning platform for the automotive field, which lays a good theoretical and practical foundation for our country's driverless technology.

关键词： Deep learning Automotive field Application value Driverless

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Belief Merging for Possibilistic Belief Bases 6th

Belief Merging for Possibilistic Belief Bases

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6th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA)

作者： Thi Thanh Luu Le Trong Hieu Tran Univ Finance & Accountancy Quangngai Vietnam VNU Univ Engn & Technol Hanoi Vietnam

ISBN: (纸本)9783030383640;9783030383633

Belief merging has received much attention from the research community with a large range of applications in Computer Science and Artificial Inteligence. In this paper, we represent a new belief merging approach for prioritized belief bases. The main idea of this method is to use two operators, namely connective strong operator and averagely increasing operator to merge possibilistic belief bases. By this way, the proposed method allows to keep more useful beliefs, which may be lost in other methods because of drowning effect. The logical properties of merging result are also analyzed and discussed.

关键词： Belief merging Possibilistic logic Prioritized belief base

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A Novel Approach to Extend KM Models with Object Knowledge Model (OKM) and Kafka for Big Data and Semantic Web with Greater Semantics 13th

A Novel Approach to Extend KM Models with Object Knowledge M...

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13th International Conference on Complex, intelligent, and Software Intensive systems (CISIS)

作者： Prabhu, C. S. R. Gandhi, R. Venkateswara Jain, Ajeet K. Lalka, Vaibhav Sanjay Thottempudi, Sree Ganesh Rao, P. V. R. D. Prasad Quantum Univ Roorkee Uttarakhand India KMIT Hyderabad Telangana India UOT Jaipur Rajasthan India KMIT CSE Hyderabad Telangana India KLU Vijayawada Andhra Pradesh India Philips R&D Bengaluru India Heidelberg Univ Heidelberg Germany KL Univ CSE Vijayawada India

ISBN: (纸本)9783030223540;9783030223533

In knowledge management (KM), everything is identified by an object and the world is a collection of objects. In the context of NLP, identifying grammar is a tedious task. Every sentence is being identified as a triplet: subject, predicate and object. The circumstantial detail of different tenses representing past and future of the grammar are very difficult to analyze. To identify such diversity of data - including streaming data, we propose a model, called Object Knowledge Model (OKM). Current scenario of RDF(S) defines metadata at every stage which is static in nature and lacks flexibility. Mainly OKM intends to provide a common framework for expressing machine-processable information with greater semantics than RDF-being modeled to identify the metadata in streams built on Kafka. This paper primarily discusses OKM grammar and how metadata can be analyzed implementing OKM. With known Stanford NLP technique plus others, the proposed OKM grammar is more flexible and demonstrates to be superior. The grammar checks genuinity of framing sentences (in various languages) as each language has its roots and connotations intrigued, and we claim that this proposed model is a better fitter for NLP understanding and projecting the merits of using them in KM models.

关键词： Knowledge management Big data Hadoop eco system Data Lakes Kafka RDF(S) Web semantics OKM

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Analysis of Existing Open Standard Framework and Ontologies in the Construction Sector for the Development of Inference Engines 13th

Analysis of Existing Open Standard Framework and Ontologies ...

引用

13th International Conference on Complex, intelligent, and Software Intensive systems (CISIS)

作者： Di Martino, B. Mirarchi, C. Ciuffreda, S. Pavan, A. Univ Campania Luigi Vanvitelli Dept Engn Aversa Italy Politecn Milan Dept Architecture Built Environm & Construct Engn Milan Italy

ISBN: (纸本)9783030223540;9783030223533

The definition of shared dictionaries able to facilitate communication in the construction sector has been an open issue long since. The advent of ICT highlighted the existing issues imposing new challenges to allow the communication between systems. Nowadays, the digital transformation in the construction sector is led by Building Information Modelling. Several efforts have been spent both in research and industry developing open standards like the industry foundation classes and related ontologies to empower interoperability. However, this paper highlights the obstacles limiting use and exchange of information at the state of the art.

关键词： Ontology

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The Car as a Transformer 3rd

The Car as a Transformer

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3rd International Conference on intelligent Human systems Integration (IHSI) - Integrating People and intelligent systems

作者： Aston, Jeremy Freire, Rui Pedro ESAD Coll Art & Design Av Calouste Gulbenkian 1011 P-4460268 Porto Portugal ESAD Idea Invest Design & Art Av Calouste Gulbenkian 1011 P-4460268 Porto Portugal

ISBN: (纸本)9783030395124;9783030395117

Vehicle design is at the forefront of innovation as we enter the next technological era (industry 4.0). This transition from traditional to alternative vehicles concerns not only the engine configuration, but the whole car as well. Electrical optimisation, autonomous driving and 'drive-by-wire', are the three main trends that are currently fostering within the automotive industry [1]. These changes provide designers with new opportunities to reimagine cars, as well as their own contributions for design [2]. ESAD College provided creative activities to stimulate the students through the design process by creating personas, scenarios and goals [5]. As a result, five different vehicle concepts were proposed, addressing 'modularity in use' (MIU).

关键词： Modularity in use Vehicle design Personas in design thinking Alternative vehicles Autonomous driving intelligent mobility Industry 4.0

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Prediction of Rumors Wide-Spreading on Social Media by Logistic Regression Modeling: Taking Water Resource Pollution Rumors Spreading as an Example 13th

Prediction of Rumors Wide-Spreading on Social Media by Logis...

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13th International Conference on Management Science and Engineering Management (ICMSEM)

作者： Li, Siqi Li, Zongmin Sichuan Univ Bussiness Sch Chengdu 610065 Peoples R China

ISBN: (纸本)9783030212483;9783030212476

Rumor spreading has become an increasingly prominent issue as the development of online social networks. Previous rumor spreading studies tend to adopt the classical epidemic models. This paper from another perspective, proposes a Logistic regression model to predict spreading probability of a rumor. Firstly, some critical factors that influence rumors spreading are identified, including counter-rumor mechanism, local socio-economic development level, information development level index, and environmental factors. After that, this paper fits a multiple logistic regression model based on three years' water pollution rumors spreading data in China, and assesses its goodness of fit. Some influential rumors in the data are analyzed. Then, this paper tests the prediction power of the proposed model. Finally, according to the significance level of the parameters in the model, as well as the tentative prediction results, this paper gives some managerial advice to prevent rumor spreading in some major cities in China.

关键词： Rumors wide-spreading Social media Logistic regression modeling Water resource Pollution

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