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Improving Weeds Detection in Pastures Using Illumination Invariance Techniques 2nd

Improving Weeds Detection in Pastures Using Illumination In...

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2nd international conference on Advances in Computing Research, ACR 2024

作者： Alyatimi, Ali Hassan Al-Dala’in, Thair Chung, Vera Anaissi, Ali Sadgrove, Edmund J. School of Computer Science The University of Sydney Camperdown Australia Jizan Saudi Arabia Western Sydney University Sydney City Campus Penrith Australia School of Science and Technology University of New England ArmidaleNSW2351 Australia

ISBN: (纸本)9783031569494

computers have various applications in relation to the classification of weeds, including computer vision. This paper demonstrates the use of illumination invariance techniques and shadow reduction in images to improve the accuracy of machine learning (ML) models using support vector machines. The paper’s main aim is to identify the benefits of image optimisation utilising adjusting dark images. More specifically, the paper uses brightness and contrast adjustment to fix images and then compares the results of a dataset that underwent image pre-processing and a dataset that did not. Ensuring the clearness of an object in an image is essential if a ML model is to identify it accurately. Many issues within image datasets can hinder the accuracy of ML classification models, for example, illumination invariance and shadowed images, which entail underexposed dark pictures being projected onto the target in the absence of light sources. The paper uses several techniques and technologies to analyse the data, including cross-validation, a confusion matrix, the pre-processing technique, the TensorFlow framework and training conducted in both the central processing unit and graphics processing units. The results of these analyses show that the brightness has significantly enhanced the accuracy of the ML model. In addition, applying image pre-processing to the shadow has resulted in a slight improvement of 1% in this regard. In conclusion, this paper presents evidence concerning ML-based solutions for improving the accuracy of classification models by enhancing images of weeds using pixel brightness transformations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Luminance

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The Role of 5G Networks in Energy-Efficient Smart Cities Development using IoT 2

The Role of 5G Networks in Energy-Efficient Smart Cities Dev...

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2nd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Govindasamy, Chinnaraj Dayana, T.R Nisha Vasu, V. Tamilarasi, A. Prakash, R.B.R. Kalaivani, R. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai602105 India Vels Institute of Science Technology and Advance Studies Department of Computer Science India St. Claret College Department of Commerce Jalahalli Karnataka Bengaluru560013 India Kongu Engineering College Department of Computer Applications Perundurai India Electrical and Electronics Engineering Koneru Lakshmaiah Education Foundation vaddeswaram522302 India AP/ECE Erode Sengunthar Engineering College India

ISBN: (纸本)9781665456302

In theory, residents in 'smart cities' would have access to a wide range of amenities designed to enhance their daily lives by making better use of public resources and providing a more satisfying experience overall. The efficiency of these services depends on the information sharing across disparate systems serving similar functions. Large amounts of data with a variety of sophisticated, application-specific needs will likely be sent throughout the information exchange process. By better management of public resources and a focus on resident comfort, infrastructure upkeep, and environmental sustainability, 'smart cities,' which rely on ICT, aim to raise the bar on service quality. Fifth-generation (5G) wireless mobile communication paves the way for a new kind of communication network that can connect everyone and everything. Impacting economies and communities, 5G will offer the connectivity infrastructure required by many smart city applications. A glimpse into the future of urban areas may be seen in the rise of 'smart cities' and the IoT. The integration of many systems aimed to monitor varied components of the smart city may be utilized to generate a more sustainable and securer city. This research study presents a construction that mixes the data from diverse systems. In order to lessen the quantity of produced traffic in the 5G network and subsequently the energy consumption, suggest the usage of data aggregation in each antenna. A summary of 5G communication networks and different 5G technologies utilized in smart cities to promote sustainability is provided. The sustainability metrics for 5G networks are then examined across the environmental, social policy, and economic aspects, as well as sub-dimensions such as energy efficiency, energy usage, carbon footprint, contamination, cost, health, safety, and security. The findings indicate that while in an effort to address sustainability in 5G technology and intelligent buildings, the bulk of research publicat

关键词： 5G mobile communication systems

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Light weight encoder-decoder for underwater images in internet of underwater things (IoUT) 2

Light weight encoder-decoder for underwater images in intern...

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2nd international conference on Artificial Intelligence and Signal Processing, AISP 2022

作者： Nair, Rashmi S. Agrawal, Rohit Domnic, S. Department of Computer Applications National Institute of Technology Tamil Nadu Tiruchirappalli India Department of Production Engineering National Institute of Technology Tamil Nadu Tiruchirappalli India

ISBN: (纸本)9781665442909

Internet of Underwater Things (IoUT) explores the applications of Internet of Things (IoT) to monitor the sea animal habitat, observe atmosphere, and predict defense and predict defense and disaster. Raw underwater images are affected by absorption and dispersal of light due to underwater environment. Low power computational devices are preferred to cut down the cost of IoUT devices. Because of underwater environment nature, transmission of underwater images captured by underwater devices is considered as a big challenge. There is a need to provide solutions to amplify color, contrast and brightness aspects of captured underwater images to provide good visual understanding. Conventional compression techniques used for terrestrial environment, causes ringing artefacts due to the variable characteristics of underwater images. Deep image compression techniques consume more computational power and time, making them least efficient for low power computational devices. In this study, a low computational power and less time-consuming image compression technique is proposed to achieve high encoding efficiency and good reconstruction quality of underwater images. The proposed technique suggests using Convolutional Neural Network (CNN) at encoder side, which compresses and retains the structural data of the underwater image. And relative global histogram stretching based technique has been used at the decoder side to enhance the reconstructed underwater image. The proposed methodology is compared with conventional methods like Joint Pictures Experts Group (JPEG), Better Portable graphics (BPG), Contrast Limited Adaptive Histogram Equalization (CLAHE) and deep learning techniques like Super Resolution Convolutional Neural Network (SRCNN) and Residual encoder-decoder methods to evaluate the reconstructed image quality. The presented work provides high quality image in comparison with both conventional and SRCNN method. © 2022 IEEE.

关键词： Convolutional neural networks

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Learner Modeling Framework Based on Learning Analytics 2

Learner Modeling Framework Based on Learning Analytics

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2nd IEEE international conference on Data Science and computer Application, ICDSCA 2022

作者： Sun, Hongtao Zheng, Qinhua Zhang, Hengguo Pan, Huiyao Administrative Data Management Center Beijing Normal University Beijing China Research Center of Distance Education Beijing Normal University Beijing China China University of Political Science and Law Network Security and Informatization Office Beijing China School of Government Beijing Normal University Beijing China

ISBN: (数字)9781665472005

ISBN: (纸本)9781665472005

Learner modeling is essential to adaptive learning, which is the trend of online learning. Learning analytics is an effective way of learner modeling. This paper suggests a learner modeling framework from the perspective of learning analytics, including the logic layer, data layer, analysis layer, and application layer and provides methodological references for the practice of learner modeling. Empirical research is carried out to verify the validity of the learner modeling framework. The forming of a learner model with the proposed framework is introduced in detail. Finally, the article highlights the critical issues of learner modeling and practical applications. Both the educational theory and platform function are the basis of learner modeling. High-quality data guarantees a high-quality learner model. Moreover, the learner features used for learner modeling should be comprehensive, operable, and reusable. © 2022 IEEE.

关键词： computer software reusability

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How transformations of representation for input data can affect the properties of induced decision reducts and rules 27

How transformations of representation for input data can aff...

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27th international conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Stanczyk, Urszula Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Decision reducts and rules belong to forms used for the representation of knowledge learnt from input data while using a rough set approach in the exploration stage. As with any patterns that capture properties of data, the size is considered as the most important indicator of their quality, as a more general and concise description allows for improved understanding and simplified interpretation. The size of a reduct is given by its cardinality, and for a rule it is a number of included conditions, both referred to as lengths. These lengths undergo transformations along with data transformations, so such processing as discretisation leads to changed characteristics of existing patterns and through them also reducts and rules. The paper presents research with contributions in the observations focused on the influence of supervised and unsupervised discretisation on properties of attributes, induced decision reducts, and rules, offering a deeper insight into relations among them. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-nd license (https://***/licenses/by-nc-nd/4.0)

关键词： Data exploration decision reduct decision rule discretisation knowledge representation rough set theory transformation

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Task-based methodology to characterise immersive user experience with multivariate data 31

Task-based methodology to characterise immersive user experi...

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IEEE conference on Virtual Reality and 3D User Interfaces (VR)

作者： Robert, Florent Wu, Hui-Yin Sassatelli, Lucile Winckler, Marco Univ Cote Azur CNRS Inria I3S Nice France Univ Cote Azur Inria Nice France Inst Univ France Paris France

ISBN: (纸本)9798350374025;9798350374032

Virtual Reality (VR) technologies enable strong emotions compared to traditional media, stimulating the brain in ways comparable to real-life interactions. This makes VR systems promising for research and applications in training or rehabilitation, to imitate realistic situations. Nonetheless, the evaluation of the user experience in immersive environments is daunting, the richness of the media presents challenges to synchronise context with behavioural metrics in order to provide fine-grained personalised feedback or performance evaluation. The variety of scenarios and interaction modalities multiplies this difficulty of user understanding in face of lifelike training scenarios, complex interactions, and rich context. We propose a task-based methodology that provides fine-grained descriptions and analyses of the experiential user experience (UX) in VR that (1) aligns low-level tasks (i.e. take an object, go somewhere) with multivariate behaviour metrics: gaze, motion, skin conductance, (2) defines performance components (i.e., attention, decision, and efficiency) with baseline values to evaluate task performance, and (3) characterises task performance with multivariate user behaviour data. To illustrate our approach, we apply the task-based methodology to an existing dataset from a road crossing study in VR. We find that the task-based methodology allows us to better observe the experiential UX by highlighting fine-grained relations between behaviour profiles and task performance, opening pathways to personalised feedback and experiences in future VR applications.

关键词： virtual reality user experience multivariate data task modeling behaviour characterisation Human-centered computing-HCI theory,concepts and models Human-centered computing-User models Computing methodologies-computer graphics-graphics systems and interfaces-Virtual reality

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Smart Home Floor Map Generation applications Based on Image Recognition

Smart Home Floor Map Generation Applications Based on Image ...

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computer graphics and Image Processing (CGIP), international conference on

作者： Suk-Un Yoon Juan Liu Huaxin Wang Minji Kim Bongjun Ko Visual Display Division Samsung Electronics Korea Samsung Electronics Samsung R&D Institute China-Nanjing China

ISBN: (数字)9798350374186

ISBN: (纸本)9798350374193

In this paper, we propose new smart home applications generating user's home floor plan and detecting devices, furniture, doors, and windows based on the image recognition of a panorama image and a hand sketch image. To generate a floor plan from a hand sketch diagram, vectorized house layout is generated after recognizing line, corner angles, and door/windows within 1.2 seconds. To calculate room shape and size on floor map generation from a panorama image, we predict the ceiling-wall boundary line of the image, where the errors of the estimated room size are less than 0.5 meters. The generated floor map on smartphone including device information and localization can be shown at the large screen devices such as smart TV or monitor.

关键词： Meters Location awareness Image recognition Three-dimensional displays Smart TV Shape Smart homes

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Overview of Application in Data Mining Techniques to QAR Data Ansys 2

Overview of Application in Data Mining Techniques to QAR Dat...

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2nd international conference on Big Data Engineering and Education, BDEE 2022

作者： Li, Baoqiang Huang, Jin Wang, Xuexuan Shi, Yu Lv, Mingyan Hu, Miaomiao Air Traffic Management College Civil Aviation Flight University of China Guanghan China College of Computer Science and Technology Civil Aviation Flight University of China Guanghan China

ISBN: (数字)9781665481847

ISBN: (纸本)9781665481847

To ensure flight safety, the Civil Aviation Administration of China (CAAC) requires commercial aircraft to be fitted with a Quick Access Recorder (QAR), which continuously records the aircraft's raw flight data and captures thousands of flight parameters. Currently there is limited awareness and application of QAR data. With the continuous development of data analysis technology, data mining methods have been applied to QAR data processing, providing strong support and guarantee for aviation safety. This paper introduces the basic theory of data mining, reviews the applications of data mining in civil aviation operational safety, flight status assessment and identification, and general aviation respectively based on the clustering results of the literature in the past 12 years, and finally summarises the current problems faced by QAR data mining and the future development direction. © 2022 IEEE.

关键词： Data mining

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A Lower Bound on the Length of Signatures Based on Group Actions and Generic Isogenies 42nd

A Lower Bound on the Length of Signatures Based on Group Act...

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42nd Annual international conference on theory and applications of Cryptographic Techniques (Eurocrypt)

作者： Boneh, Dan Guan, Jiaxin Zhandry, Mark Stanford Univ Stanford CA USA Princeton Univ Princeton NJ 08544 USA NTT Res Inc Sunnyvale CA USA

ISBN: (纸本)9783031305887;9783031305894

We give the first black box lower bound for signature protocols that can be described as group actions, which include many based on isogenies. We show that, for a large class of signature schemes making black box use of a (potentially non-abelian) group action, the signature length must be ohm(lambda(2) / log lambda). Our class of signatures generalizes all known signatures that derive security exclusively from the group action, and our lower bound matches the state of the art, showing that the signature length cannot be improved without deviating from the group action framework.

关键词： Group theory

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A Comparative Study of Implementing Intelligent Internet of Things for Creating Better Surveillance and Security in Developing Nations 2

A Comparative Study of Implementing Intelligent Internet of ...

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2nd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Ganai, Prince Tehseen Nirmal, Ekanath Sitaram Kaushik, Manish Buddhi, Dharam Alam, Tanweer Rafi, Shaik Mohammad Shri Jagdishprasad Jhabarmal Tibrewala University Department of Information Technology Rajasthan India Arts Commerce and Science College Savitribai Phule Pune University Department of Political Science Pune India S. S. Jain Subodh P. G. College Master of Computer Applications Jaipur India Uttaranchal University Uit Uttarakhand Dehradun India Islamic University of Madinah Faculty of Computer and Information Systems Madinah Saudi Arabia Sri Mittapalli College of Engineering Department of Computer Science and Engineering Andhrapradesh Guntur India

ISBN: (纸本)9781665437899

In current history, rapid digitization has opened up new technical possibilities, which have already begun to alter the major safety and security sectors and society in general. The digital revolution opened up new opportunities for progress and more effective use of scarce resources, technologies, and operations in several sectors of the safety measurements. The Internet of Things (IoT) reflects the growth of mobile phones, houses, and integrated technologies. Because the items surrounding will have a greater understanding of our interests, ambitions, and requirements, such a development will aid in the creation of a smart environment for humans. Since IoT technologies grow more common, security challenges in IoT have gotten a lot of attention from academic and industrial. IoT systems, in comparison to traditional computing environments, have greater inherent problems and, as a result, may have increased security procedures. The existing IoT design, on the other hand, does not adequately handle the heightened security statutory responsibilities by those weaknesses. Mixed methods are used for this paper to collect statistical as well as theory-based information from different sources. Primary quantitative and secondary qualitative methods are used to collect various information. © 2022 IEEE.

关键词： Internet of things

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