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检索条件"丛书名=Lecture Notes in Networks and Systems"

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The Utilization of Artificial Intelligence and Deep Learning for Identifying Vehicle Wheels 4th

The Utilization of Artificial Intelligence and Deep Learning...

引用

4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Maaroufi, Mohammed Mouhcine Stour, Laila Agoumi, Ali Demori, Julien Hassan II Univ Casablanca Fac Sci & Technol Mohammedia Proc & Environm Engn Lab BP 146 Mohammadia Morocco Hassania Sch Publ Works Civil Engn Hydraul Environm & Climate Lab Casablanca Morocco Macq Mobil Evere Belgium

ISBN: (纸本)9783031686498;9783031686504

The technology using artificial intelligence (AI) allows, through the preprocessing of video and image data, their transformation into traffic information, the recognition in abusive conditions of elements, the specification of the different characteristics of the vehicle (type, brand, model, color), object detection and tracking, automatic calibration and positioning. Algorithms for performance evaluation can evaluate recognition quality and detect malfunctions due to external factors, reduced lighting conditions, or incorrect camera installation. This article discusses the application of AI and deep learning techniques to identify vehicle wheels. It highlights the preprocessing of image and video data to extract traffic information, detect vehicle attributes, and perform object tracking. The study focuses on understanding AI and convolutional neural networks (CNNs) for image processing, emphasizing the significance of feature extraction algorithms. The research outlines the methodology for creating a dataset of annotated wheel images, selecting the YOLO detection algorithm, and using the Darknet Github framework for training and testing CNNs. It discusses the training process, including configuration, data augmentation, and evaluation metrics like Mean Average Precision (MAP) and Intersection Over Union (IOU). Finally, the article concludes with insights into the practical applications of the developed wheel detection system, suggesting future improvements and potential integrations with other projects.

关键词： Smart mobility artificial intelligence deep learning convolutional neural networks wheel

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Real-Time ATM Booth Suspicious Behavior Monitoring System 1

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Furtado, Ashlin Sayed, Rehan Nooli, Arvin Radhakrishna, Sriram Oruganti, Rishabh Venugopal, N. PES Univ Dept Comp Sci Bengaluru 560085 Karnataka India Pes Univ Dept Elect & Commun Bengaluru 560085 Karnataka India PES Univ Dept Elect & Elect Bengaluru 560085 Karnataka India

ISBN: (数字)9789819713233

ISBN: (纸本)9789819713226;9789819713233

Automated teller machine (ATM) booths are an integral part of our life, however, there has been a rise in thefts in recent years happening in these booths [1]. Currently, the action taken against these crimes gets delayed because the investigation is done after the crime is committed using the recorded footage from the CCTV cameras that are installed in the ATM booths. Hence there is a need for a solution that can alert the authorities while the crime is being committed, i.e., in real time. The proposed study aims to detect and classify the activities of a customer in the ATM booth and flag them as suspicious using various machine learning techniques. MediaPipe is employed to extract points from the person's body which are later passed through a multilayer perceptron which helps classify the pose of the person as normal or suspicious. The model has been trained on a unique dataset which has been recorded by a camera to replicate an ATM booth's CCTV cameras. This novel dataset enables us to perform an in-depth analysis of abnormal activities. Apart from detection of specific poses our study also includes features like gaze detection, multiple people detection using YOLOv3, and face covering detection using dlib.

关键词： ATM MediaPipe Multilayer perceptron Gaze tracking YOLOv3

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Day Ahead Electricity Price Forecasting with Neural networks - One or Multiple Outputs? 20th

Day Ahead Electricity Price Forecasting with Neural Networks...

引用

20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Kulinski, Wojciech Sztyber-Betley, Anna Warsaw Univ Technol Warsaw Poland

ISBN: (纸本)9783031665936;9783031665943

Electricity prices are an essential factor for industry and intelligent systems. An important part of energy trading takes place on the Day-ahead Market. Predicting prices in this market allows economically rational decisions to be made. Our study aims to model prices in the day-ahead market using neural networks. An attempt is made to reproduce the results of the paper [Marcjasz et al., 2020], where two network structures are compared: one with one output and one with 24 outputs. Our work adapts the modelling methodology to the current challenging market conditions and variable data reporting methods. We show that a structure predicting 24 values is more resilient in dynamic price conditions.

关键词： Neural networks Deep learning Electricity price forecasting Energy market

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Data Analysis, Socioeconomic Development and Communication of the Sugar Industry 1

引用

Computing Conference

作者： Tigua-Moreira, Sonia Cruz-Navarrete, Edison Molina, Lilian Clery, Arturo Univ Milagro Milagro Ecuador Univ Guayaquil Guayaquil Ecuador Univ Estatal Peninsula Santa Elena La Libertad Ecuador

ISBN: (数字)9783031622731

ISBN: (纸本)9783031622755;9783031622731;9783031622724

This work is based on the economic analysis and the current situation of the agroindustrial sector, in the city of Milagro in the Republic of Ecuador using technological tools for its study. Situation that can be analyzed, based on the expectations that this sector has in the Ecuadorian economy, so this research shows that an increase in the income level of consumers, an increase in population, changes in habits has been achieved. shopping. demand, resulting in an increase in the demand for food goods, all with the use of data processing technologies. Based on these expectations, it can be stated that the sugar sector has enormous potential, which must be taken advantage of by producers, investors and authorities, to work together and thus achieve the take-off of the development of the sugar industry, an area that has one of the largest producers of sugar in Ecuador, and its derivatives, and that in recent years has had constant growth in the production of refined sugar. The diagnosis of the current situation of the sugar industry allows us to demonstrate the importance that it has and has had for decades in the development of the local economy, so it can be noted that the sugar industry has been the engine that moves the economy for years of the city, and a strong demand for skilled and unskilled labor. All of which is thanks to current technological tools.

关键词： Data analysis Socioeconomic development Communication

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Automated Accessibility Map Construction with Two-Level Viewpoint Planning Strategy 1

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Saito, Ryo Miura, Jun Toyohashi Univ Technol Dept Comp Sci & Engn Toyohashi Aichi Japan

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

Accessibility maps are widely used for providing access information to users of wheelchairs and strollers. In an accessibility map, the location of ramps and elevators for each building is essential for planning a route, for example, from the entrance gate to a destination building. SLAM (simultaneous localization and mapping) is a standard tool for automatically making a geometrical map by a mobile robot. Once we have a map, we can manually add ramp information afterward, but this operation is inefficient, and the resultant map may not be accurate. Therefore, we develop a method of generating a SLAM map with ramp information together. Ramp structures are usually smaller than building structures, and observing the target environment (e.g., a university campus) with a single resolution is inappropriate. We thus propose a two-level viewpoint planning approach where the robot observes only ramp regions in a denser resolution. With the test in a large simulated environment, the proposed method shows a better performance with a small extra cost than the method without the viewpoint planning for ramp detection.

关键词： Viewpoint planning Accessibility map Mobile robot

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Mobile Application mDating 10th

Mobile Application mDating

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Suceska, Suad Brcanska 7 Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

Dating applications are very much and successfully used in developed countries for getting necessary information for finding an appropriate partner. Most of these applications in developed countries get professional support, especially from sociology and psychology experts. This is the reason for the commercialization of their use. Mobile application mDating enables use of dating service in Bosnia and Herzegovina. It is made for smartphones with operating system Android.

关键词： Finding a partner Dating service Mobile application mDating Android

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Fusion of Hyperspectral and Multispectral Images for Land Use Segmentation 9th

Fusion of Hyperspectral and Multispectral Images for Land Us...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Irfan, Ayesha Beijing Univ Technol Fac Informat Technol Beijing Peoples R China

ISBN: (纸本)9789819735556;9789819735563

Land use feature detection is possible through high spatial and spectral resolution images. The spectral image resolution of hyperspectral sensors is mostly high, but the spatial resolution is low. The multispectral sensor produces good spatial resolution images with poor spectral resolution. In recent years, numerous techniques have been proposed for the improvement of spatial and spectral resolution in high-quality images acquired from the same scene by combining the acquired data. For this purpose, we fused hyperspectral and multispectral images, removed distortions, and improved the quality of the images by Gram-Schmidt, one of the pan-sharpening methods. Our selected study area is in Beijing, China. The fused image generated from the same area is utilized to segment land use through the U-Net model. The model we used for this study is trained and tested fused, multispectral, and hyperspectral images, and results showed that overall accuracy is 86.88 for hyperspectral imagery, 93.28 for multispectral imagery, and 97.59 for fused imagery. The results signify the employed approach has improved both image enhancement and fusion of images. Additionally, this technique can generate an imaging output characterized by high spectral data quality and high spatial resolution.

关键词： Land use segmentation Pattern recognition Remote sensing Hyperspectral Multispectral Data fusion

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Assessing the Technological and Commercial Readiness for Innovative Projects 11th

Assessing the Technological and Commercial Readiness for Inn...

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Cseminschi, Stanislav Cojocari, Elena Ionica, Andreea Leba, Monica Florea, Vlad Univ Petrosani Petrosani Romania

ISBN: (纸本)9783031456473;9783031456480

We live in a world governed by innovation that imprints a rapid pace of change. Innovative start-up projects are the engine of these changes. The low success rates of these projects are well known and somehow assumed in the idea of fail, fail again, fail better. We learn from failure, but it's best to prepare for success. Thus, the paper proposes the use of the CloverLeaf methodology in the evaluation of innovative higher education projects. The identification of the technological, marketing, commercial and management readiness for the projects within the University of Petrosani represents the main results of the present research. These findings will be helpful in directing decisions regarding the following steps to be taken regarding the efforts to be invested based on the readiness dimension that needs to be improved, the crowdfunding campaigns (reward and equity) to be launched, and/or business accelerators that can raise the project's chances of success.

关键词： Assessment Innovation Readiness Technology

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HyMO-RF: Automatic Hyperparameter Tuning for Energy Theft Detection Based on Random Forest Classification

HyMO-RF: Automatic Hyperparameter Tuning for Energy Theft De...

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Intelligent systems Conference (IntelliSys)

作者： Coelho, Francisco J. S. Alcantara, Andre L. M. Feitosa, Allan R. S. Takeuchi, Jessica T. Lima, Ronaldo F. Silva-Filho, Abel G. Univ Fed Pernambuco Informat Ctr BR-50740560 Recife PE Brazil Eldorado Res Inst BR-13083898 Campinas SP Brazil CPFL ENERGIA BR-13087397 Campinas SP Brazil

ISBN: (纸本)9783031477201;9783031477218

To curb energy theft and identify fraudsters and other nontechnical losses, power distribution companies have used Machine Learning algorithms and a large amount of data with high granularity from electricity consumption units. Those data are collected from consumers through Advanced Metering Infrastructure (AMI) like Smart Meters (SM) being remotely collected in real time and several samples per day. In emerging countries like Brazil, most energy meters are technologically limited or electromechanical. Those devices can measure only aggregated values of energy consumption in a monthly basis. This work proposes HyMO-RF, one strategy of using a multi-objective search algorithm to improve the performance of a machine-learning model in the detection energy theft in a scenario of limited resources (AMI and SM). The proposed approach in this paper (HyMO-RF) is based on hyperparameter tuning and the main contribution is to associate multi-objective algorithms to determine an optimized combination of hyperparameters in order to maximize the classification model's performance. A real life corporate dataset was provided by a Brazilian power distribution company CPFL ENERGIATM. The data was properly anonymized and securely stored. We used NSGAII multi-objective algorithm for hyperparameters tuning, improving the Random Forest (RF) classifier's performance. Results achieved in terms of Precision and F1-score metrics were 0.83 and 0.73 respectively. An additional field study showed that the solution proposed already impacted the operation of the fraud detection team in a positive way by having an accuracy of 74% of the suspect consumer units inspected.

关键词： Energy theft Non-technical losses Hyperparameter tuning Machine learning Multi-objective algorithm

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RCBEVD: Radar-Camera Fusion in Bird's Eye View for Detection with Velocity Estimation 1

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Jia, Yansong Lee, Christina Dao Wen Ang, Marcelo H., Jr. Natl Univ Singapore Singapore Singapore

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

Radar and camera sensors are commonly used in the perception stack of autonomous driving systems due to their maturity, cost-effectiveness, and robustness. The outputs from these sensors are often fused to generate more accurate perception results, due to their complementary features. In this paper, we propose a method, RCBEVD: Radar-camera fusion in Bird's Eye View (BEV) representation for detection with velocity estimation. We introduce a novel clustering method for radar point clouds alongside a tracking algorithm to estimate the true radar point's velocity. The estimated true radar velocities are fused with 2D object detection bounding boxes to give BEV detections. RCBEVD is evaluated on the nuScenes dataset benchmark using the Average Velocity Error (AVE) and Average Precision (AP) metrics. We outperform the baseline method CenterFusion's Mean Average Velocity Error (mAVE) 0.696 m/s (-0.690 m/s), an improvement of 49.8% on the nuScenes validation dataset.

关键词： Autonomous vehicles Robotics Artificial intelligence

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