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检索条件"任意字段=18th Image Processing: Algorithms and Systems Conference, IPAS 2020"

共 258 条记录，以下是211-220 订阅

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DynaScale: An Intelligent image Scale Selection Framework for Visual Matching in Smart IoT

DynaScale: An Intelligent Image Scale Selection Framework fo...

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

作者： Bo-Lung Tsai Kwei-Jay Lin Yuheng Cao Yu Meng University of California Irvine CA USA Northeastern University Shengyang China

ISBN: (纸本)9781728176505

Localization is one of the fundamental technologies to enable location-aware services in smart cities. image feature matching plays an essential role in visual-based localization for moving IoT devices to navigate in various scenes. Conventional matching pipelines have issues with finding an accurate transformation model when a pair of to-be-matched images have a huge scale difference between the views of interested objects. the paper introduces DynaScale, a general framework that integrates existing image detection and matching algorithms with constructed image pyramids for extended matching, and selects the best matching result from the image pairs of different scales. We have designed an intelligent evaluation scheme of potential transformation models based on various tests including reasonable projections, the resembled size of region proposals, and similarities of bounded descriptors. the experimental result shows that, on selected datasets, DynaScale has 1.9 times better mean matching accuracy than existing methods from 24.32% to 45.91%, and produces about twice the number of useful, correctly matched frames in a moving robot's video stream.

关键词： Location awareness Visualization Smart cities image matching Pipelines Robot vision systems Streaming media

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11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 International conference on Artificial Intelligence Applications and Innovations, AIAI 2022

11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putt...

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11th Mining Humanistic Data Workshop, MHDW 2022, 7th 5G-Putting Intelligence to the Network Edge Workshop, 5G-PINE 2022, 1st workshop on AI in Energy, Building and Micro-Grids, AIBMG 2022, 1st Workshop/Special Session on Machine Learning and Big Data in Health Care, ML@HC 2022 and 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics, AIBEI 2022 held as parallel events of the 18th IFIP WG 12.5 International conference on Artificial Intelligence Applications and Innovations, AIAI 2022

ISBN: (纸本)9783031083402

the proceedings contain 35 papers. the special focus in this conference is on Mining Humanistic Data. the topics include: Digitally Assisted Planning and Monitoring of Supportive Recommendations in Cancer Patients;CAIPI in Practice: Towards Explainable Interactive Medical image Classification;a Deep Q Network-Based Multi-connectivity Algorithm for Heterogeneous 4G/5G Cellular systems;simulating Blockchain Consensus Protocols in Julia: Proof of Work vs Proof of Stake;Maximum Likelihood Estimators on MCMC Sampling algorithms for Decision Making;employing Natural Language processing Techniques for Online Job Vacancies Classification;Probabilistic Quantile Multi-step Forecasting of Energy Market Prices: A UK Case Study;proactive Buildings: A Prescriptive Maintenance Approach;performance Meta-analysis for Big-Data Univariate Auto-Imputation in the Building Sector;non-intrusive Diagnostics for Legacy Heat-Pump Performance Degradation;a 5G-Based Architecture for Localization Accuracy;anomaly Detection in Small-Scale Industrial and Household Appliances;an Innovative Software Platform for Efficient Energy, Environmental and Cost Planning in Buildings Retrofitting;deep Learning-Based Segmentation of the Atherosclerotic Carotid Plaque in Ultrasonic images;An Intelligent Grammar-Based Platform for RNA H-type Pseudoknot Prediction;An Automated 2D U-Net Segmentation Method for the Identification of Cancer Brain Metastases Using MRI images;the Use of Robotics in Critical Use Cases: the 5G-ERA Project Solution;fundamental Features of the Smart5Grid Platform Towards Realizing 5G Implementation;experimentation Scenarios for Machine Learning-Based Resource Management;efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases;5G for the Support of Smart Power Grids: Millisecond Level Precise Distributed Generation Monitoring and Real-Time Wide Area Monitoring;monitoring Neurological Disorder Patients via Deep Learning Based Facial Expressions An

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[Regular Paper] Implementation of an Ultrasound Platform for Proposed Photoacoustic image Reconstruction Algorithm

[Regular Paper] Implementation of an Ultrasound Platform for...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Enkhbat Batbayar Enkhbaatar Tumenjargal Chulgyu Song Woonchul Ham Electronic Division Chonbuk National University Jeonju South Korea

ISBN: (纸本)9781538650431;9781538662175

Photoacoustic tomography is a quickly growing imaging method that can provide images of high spatial resolution and high contrast at a limited depths. Medical photoacoustic processing characteristics two main components: A transducer is required to transmit laser pulses and acquire the reflected ultrasound signals and a back-end processing system that will generate the final reconstructed image. In this paper, we introduce an implementation of the receive part of proposed embedded system and briefly discuss reconstruction algorithms which are used in medical imaging systems. Furthermore, an intellectual property core (IP-core), which can be controlled and configured by a user application on Zynq-7000 System-On-Chip (SoC) via AXI-Lite Interface, that can receive multichannel digitized raw signals from Analog-Front-End (AFE) device via Low Voltage Differential Signal (LVDS), is proposed for photoacoustic imaging systems. Besides, block diagram of the system, the hardware design flow and the proposed IP-core are fully described in this paper. In order to effortlessly test and evaluate a wide variety of ultrasonic signal processing applications, 16 channel system is implemented and demonstrated by using TI AFE5816 Evaluation module (EVM) based on AFE5816 device and Xilinx ZC702 Evaluation Kit based on Zynq-7000 SoC. Apart from working on hardware, we review and commented on the proposed 3-Dimensional photoacoustic image reconstruction algorithm.

关键词： Clocks Ultrasonic imaging Acoustics image reconstruction Signal processing algorithms Receivers Hardware

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Optimized Multi-Shaped Traffic Light Detection and Signal Recognition with Guided Framework

Optimized Multi-Shaped Traffic Light Detection and Signal Re...

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International conference on Advances in ICT for Emerging Regions

作者： R.P.U.N. Rajapaksha L. Ranathunga Department of Information Technology University of Moratuwa University of Moratuwa Katubedda Sri Lanka

ISBN: (纸本)9781538673539;9781538673522

Traffic Light detection and recognition has become one of the critical research areas when it comes to autonomous driving vehicles. Developing an algorithm to detect different shaped traffic lights such as traffic lights (TLs) with arrowheads, circular shapes, horizontally and vertically oriented TLs and TLs in different illumination conditions during daytime still remains a challenge. this paper evaluates the existing algorithms, which uses heuristic or template matching based image processing methods and other learning based systems, that consumes higher time and processing power for training and map based systems and proposes a novel optimized algorithm using machine vision techniques to meet those challenges. the experiments were carried out using videos taken by front camera of vehicles. the results of the algorithm show a higher accuracy for precision and recall evaluations.

关键词： Shape image color analysis Cameras Brightness Videos Lighting Global Positioning System

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Obedience testing of the vehicles to the traffic lights in video by image processing techniques

Obedience testing of the vehicles to the traffic lights in v...

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IEEE Signal processing and Communications Applications (SIU)

作者： Özlem Morkaya Serdar Korukoğlu TÜBİTAK-EEEAG Ankara Turkey TÜBİTAK-EEEAG Kavaklıdere Ankara Ege Üniversitesi Mühendislik Fakültesi Bilgisayar Mühendisliği Bölümü İzmir Turkey

In this study, traffic light location and light color are determined to estimate whether moving vehicles obey or don't obey the traffic light by the use of image processing techniques. Application tracks vehicles in addition, it offers a solution to the problem of passing, which is often violated, while the traffic light is red. In the literature vehicle tracking applications usually work on counting the number of cars and estimating traffic congestion. A few number of applications work on recognizing of traffic signs and implement motion analysis. Establishing a solution to the problem of vehicle passing, while light is red, is also important for driving assistance systems which are currently being developed. Proposed application, finds the count of vehicles by the use of vehicle tracking and explains the implementation of the estimation about vehicles' obedience to the traffic light in a detailed way. Hence application implements motion analysis with the use of information about vehicle tracking and traffic light.

关键词： Vehicles Tracking Pattern recognition Classification algorithms conferences Real time systems Artificial intelligence

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Video denoising based on transform domain minimum mean square error

Video denoising based on transform domain minimum mean squar...

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IEEE International conference on image processing

作者： Jingjing Dai Oscar C. Au Chao Pang Feng Zou Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong China

Denoising is one of the most common and important tasks in video processing systems and abundant efforts have been made on video denoising nowadays. In this paper, we propose a novel denoising scheme based on minimum mean square error (MMSE) filter in the 2D transform domain, which we call 2DTD-MMSE. the current input noisy frame is processed block-by-block, and for every block, the current noisy observation and multiple prediction blocks found by motion estimation (ME) in denoised previous frames as well as noisy future frames constitute a 2D observed representation array. Afterwards, 2D transform is applied to every block in the representation array, and every transform coefficient of current block is estimated by weighted average of the coefficients in the same frequency position of all the transformed blocks. the weighting coefficients are adaptively determined through MMSE for every block after the estimation of statistical parameters in the transform domain. Experimental results on commonly used test sequences demonstrate that the proposed 2DTD-MMSE achieves comparable or favorable performance when compared to several state-of-the-art algorithms.

关键词： Noise reduction Noise measurement Noise image processing Wavelet transforms Estimation

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Information Fusion-2-Text: Explainable Aggregation via Linguistic Protoforms 18th

Information Fusion-2-Text: Explainable Aggregation via Lingu...

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18th International conference on Information processing and Management of Uncertainty in Knowledge-Based systems, IPMU 2020

作者： Murray, Bryce J. Anderson, Derek T. Havens, Timothy C. Wilkin, Tim Wilbik, Anna Electrical Engineering and Computer Science Department University of Missouri ColumbiaMO United States College of Computing and Department of Electrical and Computer Engineering Michigan Technological University HoughtonMI United States School of Information Technology Deakin University GeelongVIC Australia Information Systems Group of the Department of Industrial Engineering and Innovation Sciences Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9783030501525

Recent advancements and applications in artificial intelligence (AI) and machine learning (ML) have highlighted the need for explainable, interpretable, and actionable AI-ML. Most work is focused on explaining deep artificial neural networks, e.g., visual and image captioning. In recent work, we established a set of indices and processes for explainable AI (XAI) relative to information fusion. While informative, the result is information overload and domain expertise is required to understand the results. Herein, we explore the extraction of a reduced set of higher-level linguistic summaries to inform and improve communication with non-fusion experts. Our contribution is a proposed structure of a fusion summary and method to extract this information from a given set of indices. In order to demonstrate the usefulness of the proposed methodology, we provide a case study for using the fuzzy integral to combine a heterogeneous set of deep learners in remote sensing for object detection and land cover classification. this case study shows the potential of our approach to inform users about important trends and anomalies in the models, data and fusion results. this information is critical with respect to transparency, trustworthiness, and identifying limitations of fusion techniques, which may motivate future research and innovation. © 2020, Springer Nature Switzerland AG.

关键词： Information fusion

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Two automatic calibration algorithms for left ventricle boundary estimation in X-ray images

Two automatic calibration algorithms for left ventricle boun...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： J.S. Suri R.M. Harelick F.H. Sheehan Intelligent Systems Laboratory Department of Electrical Engineering University of Washington Seattle WA USA Washington University in Saint Louis Saint Louis MO US Cardiovascular Research & Training Center University of Washington Seattle WA USA

Non-homogeneous mixing of the dye with the blood in the left ventricle and low contrast in the apex zone causes pixel-based classifiers to yield boundaries which are not close physician traced boundaries. they have a systematic positional and orientational bias, with under-estimation in the apex zone. this paper develops two calibration algorithms, the identical coefficient and the independent coefficient. these algorithms transform the two sets of given training boundaries: physician traced and the classifier, to yield the off-line parameters, depending upon the number of partitions of the database. Vertices of the left ventricle boundary are then estimated on-line by applying these transformed parameters. the performance of the calibration system based on the polyline distance metric yields a mean error of 3.7 and 3.6 millimeters for above algorithms over 6/spl times/10/sup 4/ vertices in the data base of 291 patient studies. Both calibration algorithms remove the bias and reduce the boundary error in the apex zone. For end-diastole frame the system reduces the error by 8.5 millimeters in the apex zone over the pixel-based classifier boundaries produced by image processing algorithms.

关键词： Calibration X-ray imaging Heart Yield estimation Blood Partitioning algorithms Databases image processing Biomedical imaging Shape

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An Efficient Low Delay Task Scheduling Algorithm Based on Ant Colony System in Heterogeneous Environments

An Efficient Low Delay Task Scheduling Algorithm Based on An...

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

作者： Pei Yang Jing Liu Cen Chen Yucheng Ding Chunhua Deng Zeng Zeng College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Institute for Infocomm Research Singapore Hunan *** Interactive Entertainment Media Co. Ltd. Changsha China

ISBN: (纸本)9781728176505

Low delay is an important issue in a variety of applications on heterogeneous computing platforms. A great number of algorithms including heuristics as well as metaheuristics have been designed to minimize the completion time (i.e., makespan) of applications and achieved good results. However, the demand of high performance never stops. In this paper, we propose a new and efficient Ant-Colony based Low Delay Scheduling (ACLDS) algorithm to minimize the makespan of applications which can form directed acyclic graphs and are executed on a heterogeneous system. Simulated results show that our proposed algorithm is highly efficient in reducing makespan in comparison with state-of-the-art scheduling algorithms. For instance, the reduction ratio can be up to 15.2174% for a Fast Fourier Transform (FFT) benchmark.

关键词： Directed acyclic graph Smoothing methods Scheduling algorithms Fast Fourier transforms High performance computing Heuristic algorithms Scheduling

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Face Liveness Detection Competition (LivDet-Face) - 2024 18

Face Liveness Detection Competition (LivDet-Face) - 2024

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18th IEEE International Joint conference on Biometrics, IJCB 2024

作者： Igene, Lambert Hossain, Afzal Chowdhury, Mohammad Zahir Uddin Rezaie, Humaira Rollins, Ayden Dykes, Jesse Vijaykumar, Rahul Komaty, Alain Marcel, Sébastien Schuckers, Stephanie Tapia, Juan E. Aravena, Carlos Schulz, Daniel Adami, Banafsheh Karimian, Nima Nunes, Diogo Marcos, João Gonçalves, Nuno Sikošek, Lovro Batagelj, Borut Alenin, Aleksandr Alkhaddour, Alhasan Pimenov, Anton Tregubov, Artem Avdonin, Igor Kazantsev, Maxim Pozigun, Mikhail Pryadchenko, Vasiliy Schei, Nima Pabon, David Tiedemann, Manuela Clarkson University United States Idiap Research Institute Switzerland Darmstadt Germany West Virginia University Morgantown United States University of Coimbra Institute of Systems and Robotics Portugal University of Ljubljana Faculty of Computer and Information Science Ljubljana Slovenia Id R&d Inc Barcelona Spain Hummingbirds Ai FL United States Dermalog Identification Systems GmbH Hamburg Germany

ISBN: (纸本)9798350364132

Imagine a world where a copy of your face could trick the most advanced security systems. this isn't science fiction;it's a real challenge today. LivDet-Face is a competition that aims to advance the detection of attacks at the biometric sensor, known as Presentation Attack Detection (PAD). this international contest is a key benchmark in biometric security, offering an unbiased look at the latest innovations in face PAD and demonstrating progress over time in detecting and preventing sophisticated attacks. through the International Joint conference on Biometrics (IJCB) platform, LivDet-Face 2024 provides a standardized evaluation process, access to advanced Presentation Attack Instruments (PAI), and a comprehensive dataset of bona fide face images. the competition had two main categories: algorithms and systems. A total of sixteen algorithms and one system were submitted for this year's competition. Anonymous submissions topped both image and video subcategories with an ACER of 4.93% and 4.13%, respectively. In the systems category, Team Dermalog, despite being the sole submission, achieved an impressive ACER of 3.12%. © 2024 IEEE.

关键词： Biometrics

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