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International Conference on Pattern Recognition

作者： Mingzhou Song R.M. Haralick Department of Computer Science Queen''s College of City University of New York Flushing NY USA Computer Science Doctoral Program City University of New York New York NY USA

ISBN: (纸本)076951695X

Optimal quantization, a non-parametric technique for pattern recognition, determines a compact and efficient density representation of data by optimizing a global quantizer performance measure, which is a weighted combination of average log likelihood, entropy and correct classification probability. In multidimensions, we obtain the quantization grid using genetic algorithms. Smoothing is an important aspect as it affects the generalization ability of the quantizer. We propose a fast k neighborhood smoothing algorithm. Optimal quantization is much more efficient than other non-parametric methods. For not very well separated Gaussian mixture models, it produces much better results than the EM algorithm, which fails to converge to the true parameters of the underlying density.

关键词： Quantization Smoothing methods Entropy Partitioning algorithms Histograms Genetic algorithms computer science Classification tree analysis Ash Educational institutions

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Glucose Sensing Utilizing Complex-Valued Neural Networks 23

Glucose Sensing Utilizing Complex-Valued Neural Networks

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4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023

作者： Lv, Yiqi Meng, Xiang Luo, Yong Pei, Yan The Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University China and Jt. International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai China Doctoral Program Grad. Sch. of Comp. Science and Engineering Graduate Department of Computer and Information Systems University of Aizu Aizuwakamatsu Japan Computer Science Division University of Aizu Aizuwakamatsu Japan

ISBN: (纸本)9798400700705

This paper proposes a Complex-Valued Neural Network (CVNN) for glucose sensing in milli-meter wave (mmWave). Based on the propagation characteristics of millimeter wave in glucose medium, we obtain the S21 parameter of glucose with the concentration range of 0-300mg/dL in the 60-80 GHz frequency band by High Frequency Structure Simulator (HFSS) simulations. Then we combine the sensing model with a neural network to detect and predict the glucose concentration relying on the learning ability of the neural network. In the prediction of the concentration of unknown samples, the absolute error between the predicted value and the true value is within 5mg/dL, which confirms the ability of the proposed CVNN model. © 2023 ACM.

关键词： Millimeter waves

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Initial Study of Oil Palm Crop Condition Detection Through Drone Imagery: A YOLO Approach

Initial Study of Oil Palm Crop Condition Detection Through D...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Winata Nugraha Ermatita Deris Stiawan Faculty of Computer Science Doctoral Program Faculty of Engineering Universitas Sriwijaya Palembang Indonesia Department of Information System Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

Oil palm plantations in Indonesia still have many challenges, especially in terms of monitoring and mapping technology. One of the important aspects in the monitoring stage of oil palm plantations is monitoring the productivity of oil palm plants. To identify the oil palm plants, many previous studies have utilized image analysis to solve the problem. The problem is that poor image conditions can affect the architecture model to be built.[1] So in this research we do tune mapping on the image to produce a quality image. Each image data that has been improved will be feature extracted using ResNet and VGG to produce the best model. Furthermore, the classification model development process is carried out using CNN architecture as the model architecture. We also provide innovation by using object detection technology. Which uses artificial neural networks. Here we train the model using aerial video datasets of oil palm plants obtained from drones. Furthermore, to evaluate the performance of the above technique, it is proposed to use the mapping model, precision and accuracy evaluation obtained in the test phase[2]

关键词： YOLO Productivity Technological innovation Oils Multimedia systems Plantations Feature extraction Informatics Monitoring Drones

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Multi-tenant Cloud SaaS Application for a meeting to task transition via deep learning models

Multi-tenant Cloud SaaS Application for a meeting to task tr...

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Artificial Intelligence and Internet of Things (GCAIoT), IEEE Global Conference

作者： Viktor Walter-Tscharf Department of Information Engineering and Computer Science Doctoral Program Industrial Innovation Fondazione Bruno Kessler University of Trento European Institute of Innovation and Technology

ISBN: (纸本)9798350309850

Thought digitalisation and the post pandemic period online meetings increase by 12.9% and number of attendees by 13.5%. According to Zoom, Google Meets, and MS Teams they collectively increased there amount of active users from March 2020 until june 2021 by 253%. Additionally virtual meetings are becoming inefficient, unproductive and unstructured, where results are not documented correctly. The intention is to shift those statistics by revolutionising the way online meeting are held. The paper outlines the technical requirements for a user-friendly web application that allows to reproduce a virtual meeting including agreements, its participants interactions and highlighting relevant sequences, is outlined. The developed AI meeting wizard autonomously documents the discussed content in the form of notes, to-dos tasks and integrates them directly into task management, mail or calendar tools. Reinforcing the focus on the discussion by increased interaction and productivity instead of task management and note taking.

关键词： Technical requirements Productivity Pandemics Software as a service Speech recognition Internet of Things Task analysis

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Helical CT reconstruction from wide cone-beam angle data using ART

Helical CT reconstruction from wide cone-beam angle data usi...

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Brazilian Symposium on computer Graphics and Image Processing (SIBGRAPI)

作者： B.M. Carvalho G.T. Herman Doctoral Program in Computer Science The Graduate Center City College and Graduate Center City University of New York New York NY USA

We report on new results on the use of algebraic reconstruction techniques (ART) for reconstructing from helical cone-beam computerized tomography (CT) data. We investigate two variants of ART for this task: a standard one that considers a single ray in an iterative step and a block version which groups several cone-beam projections when calculating an iterative step. Both algorithms were implemented using modified Kaiser-Bessel window functions, also known as blobs, placed on the body-centered cubic (bcc) grid. The algorithms were used to reconstruct a modified 3D Shepp-Logan phantom from data collected for the PI-geometry for two different maximum cone-beam angles (/spl plusmn/9.46/spl deg/ and /spl plusmn/18.43/spl deg/). Both scattering and quantum noise (for three different noise levels) were introduced to create noisy projections. The results presented here (for both noiseless and noisy data sets) point to the fact that, as opposed to filtered backprojection algorithms, the quality of the reconstructions produced by the ART methods does not suffer from the increase in the cone-beam angle.

关键词： Subspace constraints Image reconstruction Computed tomography X-ray detection X-ray detectors Noise level Object detection Iterative algorithms X-ray imaging Sensor arrays

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A Systematic Integrated Literature Review of Clinical Data Management Platforms of HL7 FHIR

A Systematic Integrated Literature Review of Clinical Data M...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Franz Frederik Walter Viktor Walter-Tscharf Department of Information Engineering and Computer Science Fondazione Bruno Kessler University of Trento European Institute of Innovation and Technology Doctoral Program Industrial Innovation

This study is dedicated to a critical investigation of the existing approaches toward a data visualization management platform based on Fast Health Interoperability Resources (FHIR). Despite the growing popularity of FHIR, the available evidence provides a compelling reason to believe that its use is still accompanied by a significant number of technical challenges. Therefore, the development of tools to ensure its convenient visualization remains a pressing need for a variety of stakeholders operating in the healthcare industry. Results of the systematic literature review that included 26 studies provide valuable information about the most popular instruments in this area, such as the OpenEHR CKM approach. The review offers a critical discussion of the most important advantages and disadvantages of different approaches. It provides valuable recommendations for further research as well as practical recommendations concerning the best ways to utilize data visualization platforms based on FHIR. It defines the tradeoff of functionality versus the ease of dissemination as one of the most important problems facing most platforms and suggests avenues for developing additional tooling support for visualizing FHIR. The results of the research could be useful both for scientists and practitioners.

关键词： Industries Systematics Bibliographies Instruments Data visualization Pressing Medical services

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Developing architectural lighting representations

Developing architectural lighting representations

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IEEE Symposium on Information Visualization (INFOVIS)

作者： D.C. Glaser R. Tan J. Canny E. Yi-Luen Do Interdisciplinary Doctoral Program U.C. Berkeley Department of Computer Science U.C. Berkeley Department of Architecture University of Washington

This paper reports on the development of a visualization system for architectural lighting designers. It starts by motivating the problem as both complex in its physics and social organization. Three iterations of prototypes for displaying time and space varying phenomena are discussed. Fieldwork is presented to identify where in practice they will be most effective. A set of user studies, one of which is analyzed in fine-grained detail, show how building designers incorporate visualization on hypothetical design problems. This has positive implications for both energy efficiency and lighting quality in buildings.

关键词： Buildings Visualization Physics computer science Prototypes Energy efficiency computer interfaces Virtual prototyping computer architecture Extraterrestrial phenomena

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On Classifying Daylight for Design

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International Journal of Architectural Computing 2003年第2期1卷 205-217页

作者： Daniel Glaser James Peng Interdisciplinary Doctoral Program University of California at Berkeley Computer Science Division 387 Soda Hall #1776 Berkeley CA 94720 - 1776 USA Department of Electrical Engineering and Computer Sciences University of California at Berkeley Computer Science Division 387 Soda Hall #1776 Berkeley CA 94720 - 1776 USA

In this paper, we present LiQuID, a tool for clustering lighting simulation data. Photographs are useful vehicles for both describing and making assessments of architectural lighting systems. A significant barrier to using photographs during the design process relates to the sheer volume of renderings that needs to be analyzed. Although there have been efforts to produce novel visualization systems to manage large sets of photographs, this research aims to reduce the complexity by classifying data into representative prototypes. A hypothetical case study is discussed.

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Using frequent pattern mining to identify behaviors in a naked mole rat colony

Using frequent pattern mining to identify behaviors in a nak...

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25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25

作者： Imberman, Susan P. Kress, Michael E. McCloskey, Dan P. Dept. Psychology Staten Island NY 10314 United States CSI/IBR Center for Developmental Neuroscience Staten Island NY 10314 United States Technology Systems Staten Island NY 10314 United States Dept. Computer Science College of Staten Island 2800 Victory Blvd Staten Island NY 10314 United States Doctoral Program Computer Science the Graduate Center at CUNY United States

ISBN: (纸本)9781577355588

Animal behavior analysis has, in the past, taken a very low tech approach, with direct observer surveillance and automated video surveillance as the norm. These methods are insufficient when one wants to study interactions between large numbers of animals in their housing environment. In this paper we use a housing environment that has been equipped with a system of RFID sensors. RFID transponders were implanted into the study animal, the naked mole rat. The resulting data was analyzed using principal component analysis and frequent pattern mining. Results showed that these methods can identify time periods of high behavioral activity from that of low aclivity, along with which groups of animals interacted with one another. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Rats

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Classification of Land Cover from Sentinel-2 Imagery Using Supervised Classification Technique (Preliminary Study)

Classification of Land Cover from Sentinel-2 Imagery Using S...

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International Conference on Information Management and Technology (ICIMTech)

作者： Eka Miranda Achmad Benny Mutiara Ernastuti Wahvu Catur Wibowo Information Systems Department Doctoral Program in Information Technology Gunadarma University Jakarta Indonesia Faculty of Computer Science and Information Technology Gunadarma University Jakarta Indonesia Computer Science Faculty Universitas Jakarta Indonesia

This paper intended to classify land cover of high-resolution satellite image using supervised classification method. The object of this research was the land cover image of the central java area in Indonesia which chosen as an area observed with the cloud cover consideration. The Satellite image was obtained from Sentinel-2 through https://***. Supervised Classification and ArcMap 10.5 was used to classified image object. This research classified the land cover into four classifications class namely Water, Forest, Urban and Bare Land due to show the main classes in the Land Cover Classification of RSNI-l National Standardization Body of Indonesia, RSNI-l was used as reference for classification process. The confusion matrix used to calculate classification accuracy value. Subsequently, confusion matrix results compared to the truth information. The truth information was derived from the actual value of RASTERVALUE obtained from Google Earth. This research shown supervised classification maximum-likelihood classification has been classified land cover into four class (forest, water body, urban and bare land) with overall accuracy = 1 and kappa value = 0.4896. This result showed this research got moderate kappa accuracy value but high overall accuracy value. High accuracy value reached due to fully supervised experiment during classification process.

关键词： Satellites Forestry Training Java Probability Standardization Vegetation mapping

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