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5th International Conference on Document Analysis and Recognition, ICDAR 1999

作者： Müller, Stefan Eickeler, Stefan Rigoll, Gerhard Department of Computer Science Faculty of Electrical Engineering Gerhard-Mercator-University Duisburg Germany

ISBN: (纸本)0769503187

In this paper, we propose an integrated approach to color and shape based retrieval which enables the user to search a color image database intuitively by presenting simple sketches. Each of the images is represented by a Hidden Markov Model (HMM) which has been concatenated with modified filler models in order to obtain scale and rotation invariance properties. These properties are particularly important when using query by sketch due to the skew which occurs naturally in human handwriting and in drawings. The use of streams (sets of features that are assumed to be statistically independent) within the HMM framework allows the integration of shape and color derived features into a single model, thereby allowing one to control the influence of the different streams via stream weights. The approach has been evaluated on a color image database containing 120 different isolated objects with arbitrary orientation and showed good retrieval results with several users. Furthermore, the use of HMMs allows efficient pruning and thus a fast retrieval even with large databases. © 1999 IEEE.

关键词： Color

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Retraction notice to “Neural network-based optimization of hydrogen fuel production energy system with proton exchange electrolyzer supported nanomaterial” [Fuel 332 (2023) 125827]

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Fuel 2025年 391卷

作者： Tao Hai Kosar Hikmat Hama Aziz Jincheng Zhou Hayder A. Dhahad Kamal Sharma Sattam Fahad Almojil Abdulaziz Ibrahim Almohana Abdulrhman Fahmi Alali Teeba Ismail Kh Sadok Mehrez Anas Abdelrahman School of Computer and Information Qiannan Normal University for Nationalities Duyun Guizhou 558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Duyun Guizhou 558000 China Institute for Big Data Analytics and Artificial Intelligence (IBDAAI) Universiti Teknologi MARA Shah Alam Selangor 40450 Malaysia Department of Chemistry College of Science University of Sulaimani Qlyasan Street Kurdistan Region 46001 Iraq Department of Medical Laboratory of Science College of Health Sciences University of Human Development Sulaimaniyah Iraq Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan Duyun 558000 China Mechanical Engineering Department University of Technology Baghdad Iraq Institute of Engineering and Technology GLA University Mathura Uttar Pradesh 281406 India Department of Civil Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Computer Engineering College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq Department of Mechanical Engineering College of Engineering at Al Kharj Prince Sattam bin Abdulaziz University 16273 Saudi Arabia Department of Mechanical Engineering University of Tunis El Manar ENIT BP 37 Le Belv’ed‘ere Tunis 1002 Tunisia Department of Chemical Engineering Faculty of Engineering & Technology Future University in Egypt New Cairo 11500 Tunisia

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Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

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computers, Materials & Continua 2022年第9期72卷 4303-4321页

作者： Saman Riaz Ali Arshad Shahab S.Band Amir Mosavi Department of Computer Science National University of TechnologyIslamabad44000Pakistan Department of Computer Science Institute of Space TechnologyIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliu64002YunlinTaiwan Faculty of Civil Engineering Technische Universitat DresdenDresden 01069Germany

The way towards generating a website front end involves a designersettling on an idea for what kind of layout they want the website to have, thenproceeding to plan and implement each aspect one by one until they haveconverted what they initially laid out into its Html front end form, this processcan take a considerable time, especially considering the first draft of the designis traditionally never the final one. This process can take up a large amountof resource real estate, and as we have laid out in this paper, by using a Modelconsisting of various Neural Networks trained on a custom dataset. It can beautomated into assisting designers, allowing them to focus on the other morecomplicated parts of the system they are designing by quickly generating whatwould rather be straightforward busywork. Over the past 20 years, the boomin how much the internet is used and the sheer volume of pages on it demands ahigh level of work and time to create them. For the efficiency of the process, weproposed a multi-model-based architecture on image captioning, consisting ofConvolutional neural network (CNN) and Long short-term memory (LSTM)models. Our proposed approach trained on our custom-made database can beautomated into assisting designers, allowing them to focus on the other morecomplicated part of the system. We trained our model in several batches overa custom-made dataset consisting of over 6300 files and were finally able toachieve a Bilingual Evaluation Understudy (BLEU) score for a batch of 50hand-drawn images at 87.86%.

关键词： Deep learning wireframes front-end low fidelity high fidelity design process html computer vision dsl

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Vehicles congestion control in transport networks using an adaptive weight model

Vehicles congestion control in transport networks using an a...

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1st International Conference on Internet of Vehicles, IOV 2014

作者： Jiang, Bin Xu, Xiao Yang, Chao Li, Renfa Terano, Takao College of Computer Science and Electronic Engineering Hunan University China Department of Computational Intelligence and Systems Science Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology Japan

ISBN: (纸本)9783319111667

This paper proposed an adaptive weight congestion control model in a vehicle transport network. Our focus was to construct a quantitative index series to describe the network congestion distribution, and to shunt vehicles on seriously congested links based on such index sequence. We achieved this goal by combing both feedback and iteration strategy in the congestion control field. First, we developed an agent based model which captured the nonlinear feedback mechanism between the vehicle routing behavior and the road congestion state. Then, the model implemented an adaptive intersection weight adjustment mechanism based on the evolutionary congestion degree of the nearby links, through which to achieve congestion distribution evaluation and network congestion control at the same time. The simulation results verified the validity of our model for congestion control under predefined networks, and proved an applicability of the intersection weight sequence as a measurement for the congestion degree and distribution of road networks. © 2014 Springer International Publishing Switzerland.

关键词： Vehicles

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Faster R-CNN with inception v2 for fingertip detection in homogenous background image

Faster R-CNN with inception v2 for fingertip detection in ho...

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International Conference on Information System, computer science and engineering 2018, ICONISCSE 2018

作者： Alamsyah, Derry Fachrurrozi, Muhammad STIMIK MDP Palembang Indonesia Department of Computer Engineering Faculty of Computer Science Universitas Sriwijaya Indonesia

Fingertip Detection is a versatile research field in computer vision, since it has multiple purpose such as natural user interface, robotic, 3D simulation etc. It is a challenging research field in computer vision. There are some hand segmentation methods, pre-processing phase, was conducted to provide area of fingertip detection in image. However, in this research, fingertip detection can be done by directly find the fingertip itself. This approach cut off preprocessing phase by using Faster R-CNN method and inception V2 architechture directly to find the fingertip in image. With a homogenous background as a simple input image, this approach showed a good accuracy in its performance. It has 90% and 91% accuracy in way to detect fingertip for both male and female hand datasets. More over, exchanging male and female model toward to male and female dataset gave 94% and 92% accuracy that showed the different pattern between both. © Published under licence by IOP Publishing Ltd.

关键词： computer vision

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Crime Prediction using Machine Learning Algorithms 15

Crime Prediction using Machine Learning Algorithms

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15th International Conference on Advances in Computing, control, and Telecommunication Technologies, ACT 2024

作者： Chitteti, Chengamma Kunapareddy, Pranathi Dharani, M. HimaKeerthi, Bapathi Sravani, Chintapatla Chilukuri, Geethika Tirupati India Tirupati India Department of Computer Science and Systems Engineering Sree Vidyanikethan Engineering College Tirupati India

ISBN: (纸本)9798331300579

Technology improvements have changed how crimes are solved, which has led to more collaborative study into how criminals act. "Prophet," an additive model-based method for predicting complicated, nonlinear time series data, such as crime actions, is presented. It does a good job of capturing time trends like holiday and seasonal affects. Using Prophet along with machine learning methods like Bayesian Regressor, Logistic Regression, Decision Tree, Gradient Boosting, Random Forest, Voting Regressor, KNN, LSTM, and Neural Network makes it more accurate at predicting crimes. With these tools, police can proactively decide how to use their resources and stop crime, which means that neighborhoods will be better. This essay shows how new technologies and models that are based on data are changing the way crimes are solved, starting a new era of preventing crimes and keeping communities safe. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

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Improved Bat Algorithm with Deep Learning-Based Biomedical ECG Signal Classification Model

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computers, Materials & Continua 2023年第2期74卷 3151-3166页

作者： Marwa Obayya Nadhem NEMRI Lubna A.Alharbi Mohamed K.Nour Mrim M.Alnfiai Mohammed Abdullah Al-Hagery Nermin M.Salem Mesfer Al Duhayyim Department of Biomedical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science and Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia

With new developments experienced in Internet of Things(IoT),wearable,and sensing technology,the value of healthcare services has *** evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based *** Electrocardiogram(ECG)signals are generally utilized in examination and diagnosis of Cardiovascular Diseases(CVDs)since it is quick and non-invasive in *** to increasing number of patients in recent years,the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from *** such scenario computer-assisted automated diagnostic tools are important for classification of ECG *** current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECGSignal Classification(IBADL-BECGC)*** accomplish this,the proposed IBADL-BECGC model initially pre-processes the input ***,IBADL-BECGC model applies NasNet model to derive the features from test ECG *** addition,Improved Bat Algorithm(IBA)is employed to optimally fine-tune the hyperparameters related to NasNet ***,Extreme Learning Machine(ELM)classification algorithm is executed to perform ECG classification *** presented IBADL-BECGC model was experimentally validated utilizing benchmark *** comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.

关键词： Data science ECG signals improved bat algorithm deep learning biomedical data data classification machine learning

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Analysis of Workloads for Cloud Services 7

Analysis of Workloads for Cloud Services

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7th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data science, BCD 2022

作者： Sankaran, Lakshmi Saleema, J.S. Suleiman, Basem Department of Computer Science Bengaluru India University of Sydney Faculty of Engineering Sydney Australia

ISBN: (数字)9781665465823

ISBN: (纸本)9781665465823

Capturing best quality datasets for a study is the first evidence for better outcomes of research. If the analysis are based on such datasets, then the metrics, the characteristics and few factors determines proof point for well proven theories. Hence it is obvious that we rely on the best possible ways to arrive at such data acquiring sources. It can be either based on historical techniques or from the innovations in application of it to industry. This paper introduces a mapping framework for analyzing, and characterizing data previously used by research community and how they are made to fit for Cloud systems, i.e. using 'workloads' and 'datasets' as the 'refined definitions'. It was contributed in the past two decades within the scientific community setting their own workflow analysis mechanisms. The framework thus is validated by acquiring a sample workload per layer of cloud. The sources are form the literature that are available from existing scientific theories. These workloads are then experimented against the three tiers of the cloud computing ie., IaaS(Infrastructure as a Service), PaaS(Platform as a Service), & SaaS(Software as a Service). The selected data is analyzed by the authors for an offline model presented here based on the Machine Learning tool-kits. There are future studies planned for and to be experimented in a cloud auto scaled environment with online model as well. © 2022 IEEE.

关键词： Platform as a Service (PaaS)

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Feasible NPC Hiding Behaviour using Goal Oriented Action Planning in case of Hide-and-Seek 3D Game Simulation 4

Feasible NPC Hiding Behaviour using Goal Oriented Action Pla...

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Suyikno, Dimas Adi Setiawan, Abas Informatics Engineering Department Computer Science Faculty Dian Nuswantoro University Semarang Indonesia

ISBN: (纸本)9781728122076

Non-Playable Characters (NPC) in the digital game are a necessary component to make the game mechanic more attractive. One common feature of most NPC in games is NPC that can hide, especially in stealth-oriented games. NPC needs to stay hidden to avoid players or something. The hiding strategies on NPC is more challenging to build related to the complexity of the game mechanic. Active hiding situation can found on hide-and-seek game. NPC as a hider in hide-and-seek game has complex behavior such as observing seeker, finding the safe place, moving to another hiding place, securing itself after being discovered by the seeker, and deciding to run away to the base. In this work, we proposed to use Goal-Oriented Action Planning (GOAP) with placement limitation (maximum two NPC in one hiding place) and unlimited placement to modeling the NPC hiding behavior. The GOAP NPC is effective to make hiding strategies through hide-and-seek game simulation. © 2019 IEEE.

关键词： Mechanics

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Enhanced Physical Layer Security for Full-Duplex Symbiotic Radio with AN Generation and Forward Noise Suppression

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IEEE Transactions on Communications 2024年第7期72卷 3905-3918页

作者： Jin, Chi Chang, Zheng Hu, Fengye Chen, Hsiao-Hwa Hamalainen, Timo University of Jyväskylä Faculty of Information Technology Jyväskylä40014 Finland University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Jilin University College of Communication Engineering Changchun130012 China National Cheng Kung University Department of Engineering Science Tainan70101 Taiwan

Due to the constraints on power supply and limited encryption capability, data security based on physical layer security (PLS) techniques in backscatter communications has attracted a lot of attention. In this work, we propose to enhance PLS in a full-duplex symbiotic radio (FDSR) system with a proactive eavesdropper, which may overhear the information and interfere legitimate communications simultaneously by emitting attack signals. To deal with the eavesdroppers, we propose a security strategy based on pseudo-decoding and artificial noise (AN) injection to ensure the performance of legitimate communications through forward noise suppression. A novel AN signal generation scheme is proposed using a pseudo-decoding method, where AN signal is superimposed on data signal to safeguard the legitimate channel. The phase control in the forward noise suppression scheme and the power allocation between AN and data signals are optimized to maximize security throughput. The formulated problem can be solved via problem decomposition and alternate optimization algorithms. Simulation results demonstrate the superiority of the proposed scheme in terms of security throughput and attack mitigation performance. 0090-6778 © 2024 IEEE.

关键词： Backscattering

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