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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VI"

共 15618 条记录，以下是4281-4290 订阅

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Towards Environmentally Adaptive Odor Source Localization: Fuzzy Lévy Taxis Algorithm and Its Validation in Dynamic Odor Plumes

Towards Environmentally Adaptive Odor Source Localization: F...

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International conference on Advanced Robotics and Mechatronics (ICARM)

作者： Xinxing Chen Jian Huang Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

In this paper, we propose a bio-inspired Fuzzy Lévy Taxis algorithm to solve the robotic odor source localization problem in dynamic odor plumes. According to the proposed algorithm, the robot is programmed to move for a length with a turning angle at each step until reaching the odor source. The movement length and the turning angle follow two specific probability distribution, of which the parameters are adaptive through a fuzzy logic system. The proposed algorithm was compared with the Adaptive Lévy Taxis algorithm in simulated pseudo-Gaussian plumes. Our proposed algorithm shows a higher success rate and efficiency. The algorithm has also been systematically evaluated in simulated filament-based odor plumes under various environmental conditions. The results revealed that the performance of the proposed algorithm is consistently good in various environmental conditions in terms of success rate, number of steps and distance overhead to find the odor source.

关键词： Public transportation Heuristic algorithms Turning Robot sensing systems Adaptation models Fuzzy systems

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Translation Russian Cyrillic to Latin Alphabet using Random Forest Algorithm

Translation Russian Cyrillic to Latin Alphabet using Random ...

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International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC

作者： Muhammad Mufti Ramadhan Budhi Irawan Casi Setianingsih School of Electrical Engineering Telkom University

ISBN: (数字)9781728184487

ISBN: (纸本)9781728184494

Russian language is ranked as the sixth most spoken language in the world. It shows a high interest in the world population to use and learn the language. The Russian language has different alphabets from the Indonesian language, which is called Cyrillic. It has a different shape from the alphabet in general, which makes some obstacles to learn, understand and pronounce it.. Currently, technology is growing fast, and it changed people's lifestyles to be more practical and mobile so that the smartphone becomes one of the society's needs. Android is one of the most used operating systems in a smartphone nowadays, so the Capture to Translate was built in android-based. Capture to Translate is a media which is designed as a solution for those problems. The system was made based on image processing, the feature extraction process, and artificial intelligence using Random Forest algorithm classification with interface Android mobile application that utilizes the camera as an input device. This system has the highest accuracy of 93.33% at one syllable, 85% at two syllables, and 84.76 % in 3 syllables.

关键词： Shape Operating systems Sociology Classification algorithms Statistics Random forests Testing

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SCALPsim. a tool for modeling asynchronous Self-Organizing 3-D NoC architectures

SCALPsim. a tool for modeling asynchronous Self-Organizing 3...

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IEEE International conference on Electronics, Circuits and systems (ICECS)

作者： Diego Barrientos Claudio Sousa Andres Upegui Bernard Girau InIT HEPIA University of Applied Sciences of Western Switzerland Geneva Switzerland Université de Lorraine LORIA UMR 7503 CNRS LORIA UMR 7503 vandoeuvre-les-Nancy France

ISBN: (数字)9781728160443

ISBN: (纸本)9781728160450

Manycore architectures are mainly composed of a very large amount of computing nodes interconnected with a multiplicity of links usually forming a NoC-like mesh architecture. High-speed links permit to obtain a higher throughput but are much more expensive than normal links, making the interconnection of the system a cost/performance trade-off. Simulating such architectures is very important in order to characterise the optimal network topology for a given problem. In this work we introduce SCALPsim: a simulation framework permitting to evaluate routing algorithms and network properties in 1-D, 2-D and 3-D regular mesh topologies simultaneously using links of different characteristics in terms of latency and throughput. These features are particularly interesting in large scale systems with processing elements grouped into clusters, where communication properties differ largely inside and between clusters. This paper presents the framework and an application based on Cellular Self-Organizing Maps - CSOM.

关键词： Neurons image coding Computer architecture Scalp Topology Computational modeling Routing

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Non-Reference image Quality Assessment Based on Noise Estimation 25

Non-Reference Image Quality Assessment Based on Noise Estima...

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25th International conference on systems, Signals and image processing (IWSSIP)

作者： Buczkowski, Mateusz Fac Elect & Telecommun Chair Telecommun Syst & Optoelect Poznan Poland

ISBN: (纸本)9781538669792

In this paper a method for estimating mean opinion score for noisy images is presented. The focus is to create a robust method, which is not suited to the single image database. Algorithm is validated using three different databases, which shows that it is more generic than other methods. Moreover, proposed solution works as non-reference image quality assessment algorithm, which means that only distorted image is used for evaluation. Results obtained with proposed method are compared with two other algorithms designed for non-reference IQA.

关键词： Databases image quality Noise measurement Correlation Distortion Estimation Signal processing algorithms"

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IOT Based Smart Water Monitoring Using image processing 6th

IOT Based Smart Water Monitoring Using Image Processing

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6th International conference on Frontier Computing, FC 2018

作者： Chang, Jieh-Ren Agarwal, Nakul Bao, Yipeng Sharma, Abhishek Department of Electronic Engineering National Ilan University Yilan Taiwan Computer Science and Engineering The LNM Institute of Information Technology Jaipur India

ISBN: (纸本)9789811336478

Several smart utility meter systems as well as their communication networks were proposed or created but they could be cost a lot. This study explores simple IOT based water monitoring to control water resource without changing the existing water meter. It is suggested simply to hangs on a smart reader which captures images from camera and performs processing and computer vision algorithms to predict reading from the image. Dial pointers’ readings are predicted by calculating the pointers’ angle. For mechanical counters, digit recognition is performed. Two types of classifiers—soft-max and a two-layer artificial neural network are used in this study. The experimental results show that the accuracy of the two-layer artificial neural network with 98.932% recognition accuracy is better than soft-max 75.679%. The identified data can be stored in the Database via the Web service, and the mobile device APP can be used to monitor the result of water usage and the water fee. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Network layers

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An investigation of burr formation and cutting parameter optimization in micro-drilling of brass C-360 using image processing 2nd

An investigation of burr formation and cutting parameter opt...

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2nd International conference on Data Engineering and Communication Technology, ICDECT 2017

作者： Pansari, Shashank Mathew, Ansu Nargundkar, Aniket Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Symbiosis Institute of Technology Symbiosis International University Pune India

ISBN: (纸本)9789811316098

A lot of research has been done in area of conventional micro-drilling but the measurement techniques for measuring burr size and holes circularity were either very expensive or inaccurate. This paper attempts to investigate role of input parameters like the spindle speed and the feed rate on burr height and burr thickness at hole exit for Brass C-360, which is a widely used material in micro-fabrication. The measurements were taken from scanning electron microscope (SEM) images of micro-drilled holes using image processing which makes the measurement simple, fast, and accurate. All the experiments were conducted using response surface methodology to develop second-order polynomial models for burr thickness and height of burr. Optimization by using multi-objective genetic algorithm and cohort intelligence algorithm using MATLAB is done to generate optimum output results. All the micro-hole SEM images were analyzed to detect the types of burrs formed during different experiments. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Genetic algorithms

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A Google Colab Based Online Platform for Rapid Estimation of Real Blur in Single-image Blind Deblurring

A Google Colab Based Online Platform for Rapid Estimation of...

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International conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Ihsan Ali Aftab Khan Muhammad Waleed Department of Computer Systems Engineering University of Engineering and Technology (UET) Peshawar Pakistan

ISBN: (数字)9781728168432

ISBN: (纸本)9781728168449

Referenceless or Blind image Deblurring (BID) is a challenging task in image restoration, because of the absence of previous information about the blurring process. In BID, the Point Spread Function (PSF) that causes blur is unknown and finding it is a challenging task to do. In contrast, reference-based image deblurring techniques are better in terms of achieving deblurred images, as in such cases we know the cause of blur and many filters and methods get the job done easily. In real life imaging, the presence of blur is caused due to many reasons including motion, defocus, atmospheric turbulence and noise in capturing device. Removing such blur to produce sharp images is very important in many cases as of today's technological driven era demands for images of unspoiled quality. This paper presents a method to eliminate blur in the fastest way. The scheme is devised to use a Genetic Algorithm (GA) on Google Colab to find PSF of the blur kernel. This work tries to estimate the parameters of blurring using quality score minimizing. Once the PSF is estimated, the Wiener filter is used for deblurring in Google Colab. This scheme presents the implementation of the algorithm on Google Colab to use GPU for achieving parallelism and reduce implementation time. Validation of the work has been carried out on different images and the system achieved marked improvements over existing approaches. The work presented is simple and efficient which requires no former information about the original sharp image or deblurring process.

关键词： Graphics processing units Internet Matlab image restoration Wiener filters Biological cells Genetic algorithms

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Estimation of Wildfire Size and Location Using a Monocular Camera on a Semi-autonomous Quadcopter 12th

Estimation of Wildfire Size and Location Using a Monocular C...

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12th International conference on Computer vision systems (ICVS)

作者： de Paula, Lucas Goncalves Hyttel, Kristian Geipel, Kenneth Richard Gil, Jacobo Eduardo de Domingo Novac, Iuliu Chrysostomou, Dimitrios Aalborg Univ Dept Mat & Prod Fibigerstr 16 DK-9220 Aalborg Denmark Aalborg Univ Dept Mat & Prod Robot & Automat Grp Fibigerstr 16 DK-9220 Aalborg Denmark

ISBN: (纸本)9783030349950;9783030349943

This paper addresses the problem of estimating the location and size of a wildfire, within the frame of a semi-autonomous recon and data analytics quadcopter. We approach this problem by developing three different algorithms, in order to accommodate this problem. Two of these taking into the account that the middle of the camera's FOV is horizontal with respect to the drone it is mounted. The third algorithm relates to the bottom point of the FOV, directly under the drone in 3D space. The evaluation shows that having the pixels correlate to ratios in percentages rather than predetermined values, with respect to the edges of the fire, will result in better performance and higher accuracy. Placing the monocular camera horizontally in relation to the drone will provide an accuracy of 68.20%, while mounting the camera with an angle, will deliver an accuracy of 60.76%.

关键词： Wildfire recognition Quadcopter analytics image processing Area estimation

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Robotic Vehicle for Automated Detection of Leaf Diseases

Robotic Vehicle for Automated Detection of Leaf Diseases

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IEEE International conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Aamina Nooraiyeen Dept. of Electronics and Communication Engg. JSS Science and Technology University Mysuru Karnataka India

ISBN: (数字)9781728168289

ISBN: (纸本)9781728168296

Currently, the demand for automated technology is increasing rapidly. People are trying to find sources that make their work easier, errorless and fast. One such recent trend in technology that aims to aid people in this purpose, is the automated robotic technology. An autonomous robot can perceive changes in its environment, make decisions based on how it has been programmed to recognize these changes and then actuates a predefined movement. In this paper, one such application of autonomous robots for plant leaf disease detection has been presented. The conventional method for detection of leaf diseases is through naked eye observation, which is highly unreliable and inaccurate. The proposed project deals with the development of an automated voice controlled robotic car built extensively using the micro controller and image sensor network that helps in detecting the leaf diseases affecting a plant (like basil, which is considered in this paper) within a garden. Upon detection of the disease, using image processing, the system alerts the user about the prevalent leaf diseases in the plant along with a set of measures to counter them. One of the major advantage of this system is that, it uniquely integrates the mobility of the robot in rough terrain with the simple K clustering and SVM algorithm for accurate detection of the leaf disease without much human intervention. The overall impact would be a user friendly voice automated robotic vehicle which eases the process of plant leaf disease detection.

关键词： Diseases Clustering algorithms Feature extraction image segmentation Robot sensing systems image color analysis

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Radiology reports automated annotation performance: rule-based machine learning vs deep learning

Radiology reports automated annotation performance: rule-bas...

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3rd Smart Cities Symposium (SCS 2020)

作者： A. Sahl S. Hasan King Khalid University Computer Science Dept. Guraiger Abha 62529 Saudi Arabia Universiti Teknologi Malaysia Sultan Ibrahim Chancellery Building Jalan Iman 81310 Skudai Johor Malaysia

Currently the availability of medical images data itself is not a challenge, but the acquisition of relevant annotations/labelling for these images is. An unsolved challenge in medical image analysis and its related radiology reports is to turn the radiology reports into an accurate annotations or structured labels in an automated manner using Natural Language processing (NLP). Traditional rule-based Machine Learning (ML) and Deep Learning (DL) algorithms are two approaches which were used in the extraction and annotation of radiology text reports. This paper provides a comparison of the performance of traditional rule-based machine learning to that of using deep learning algorithms in the extraction and annotation of radiology text reports using natural language processing (NLP). It presents an accurate analysis of the two discussed approaches and supports such with critical evidence related to the effects both approaches have on the issue of radiological reporting. According to the evaluation of the obtained data, the research concludes that Deep Learning (DL) models perform with higher efficiency than both the TML and validated NLP classifiers in terms of accuracy in extracting the required text information from the free-text radiology reports.

关键词： medical information systems text analysis radiology natural language processing deep learning (artificial intelligence) pattern classification

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