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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131-140 订阅

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Differential method of multidimensional signals compression based on the adapted parameterized interpolation algorithm 6

Differential method of multidimensional signals compression ...

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6th International conference Information Technology and Nanotechnology. Session image processing and Earth Remote Sensing, ITNT-IPERS 2020

作者： Maksimov, Aleksey Gashnikov, Mikhail Samara National Research University Samara Russia Samara National Research University Image Processing Systems Institute of RAS Branch of the FSRC "Crystallography and Photonics" RAS Samara Russia

In this paper, parameterized algorithms of multidimensional signal interpolation are adapted for use as part of differential compression methods. these methods are based on the efficient coding of quantized differences between the initial and interpolated signal samples during sequential signal scanning. the proposed interpolators are based on the classification of signal samples and the use of various interpolation formulas within the classes. the sample classifier and its training procedure and a set of interpolating functions for the compression method are described. the results of experimental research on real multidimensional signals confirm that the use of an adapted parameterized interpolator leads to an increase in the efficiency of the differential compression method. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： image enhancement

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All-IDB: the acute lymphoblastic leukemia image database for image processing

All-IDB: The acute lymphoblastic leukemia image database for...

引用

IEEE International conference on image processing

作者： Ruggero Donida Labati Vincenzo Piuri Fabio Scotti Department of Information Technology Università degli Studi di Milano Crema Italy

the visual analysis of peripheral blood samples is an important test in the procedures for the diagnosis of leukemia. Automated systems based on artificial vision methods can speed up this operation and increase the accuracy and homogeneity of the response also in telemedicine applications. Unfortunately, there are not available public image datasets to test and compare such algorithms. In this paper, we propose a new public dataset of blood samples, specifically designed for the evaluation and the comparison of algorithms for segmentation and classification. For each image in the dataset, the classification of the cells is given, as well as a specific set of figures of merits to fairly compare the performances of different algorithms. this initiative aims to offer a new test tool to the image processing and pattern matching communities, direct to stimulating new studies in this important field of research.

关键词： Blood image segmentation Microscopy Cells (biology) Classification algorithms conferences

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Optical Stealth Algorithm Under Photoelectric Countermeasures and Its Effectiveness Evaluation 18th

Optical Stealth Algorithm Under Photoelectric Countermeasure...

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18th International conference on Intelligent Information Hiding and Multimedia Signal processing, IIH-MSP 2022

作者： Yang, Zhonglin Jiang, Yutong Li, Junbao Li, Qiong Department of Automatic Test and Control School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China China North Vehicle Research Institute 4 HuaiShuling Fengtai District Beijing China

ISBN: (纸本)9789819901043

With the diversification of reconnaissance equipment and methods in the military field, optical stealth technology has become a hot spot in military research under the operational needs of optoelectronic confrontation. An improved self-adaptive visible light and infrared waveband stealth algorithm is proposed here, and its effectiveness under photoelectric confrontation is evaluated. the current digital camouflage design method is mainly through background color mixing, image segmentation, spot combination, etc. It has the defects of smooth and clear edge contour, fixed color/texture scene, and cannot adapt to complex texture background or multiple types of scenes. An improved digital camouflage design method based on fuzzy C-means clustering (FCM) image processing technology is proposed to obtain the color characteristics of the background image. then, the color block types of the camouflage spots are acquired to reduce the loss of texture information of the background image caused by clustering or segmentation to avoid the phenomenon of clear boundaries caused by single region segmentation. the results show that the use of adaptive optical stealth algorithms in the visible and infrared bands can reduce the probability of being discovered in optoelectronic countermeasures, thereby gaining a head start. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image enhancement

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AINoC: New Interconnect for Future Deep Neural Network Accelerators 16th

AINoC: New Interconnect for Future Deep Neural Network Accel...

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16th International Workshop on Design and Architecture for Signal and image processing (DASIP) held jointly with the 18th HiPEAC conference

作者： Krichene, Hana Prasad, Rohit Mouhagir, Ayoub Univ Paris Saclay List CEA F-91120 Palaiseau France

ISBN: (纸本)9783031299698;9783031299704

Data exchanges can be significant in the Deep Neural Network (DNN) algorithms. the interconnection between computing resources can quickly have a substantial impact on the overall performance of the architecture and its energy efficiency. Similarly, access to the different memories of the system, with potentially high data sharing, is a critical point. To overcome these problems, in this paper, we propose a new interconnect network, called AINoC, for future DNN accelerators, which require more flexibility and less power consumption to facilitate their integration into artificial intelligence (AI) edge systems. AINoC is based on (1) parallel routing that ensures communication/computation overlap to improve performance and (2) data reuse (filters, image inputs, and partial sums) to reduce multiple memory accesses. In the experiment section, AINoC can speedup LeNet5 convolution layers by up to 71.74x in latency performance w.r.t. a RISC-V-based CPU and also speedup MobileNetV2 convolution layers by up to 2.35x in latency performance w.r.t. a dataflow architecture featuring row-stationary execution style. AINoC provides any-to-any data exchange with wide interfaces (up to 51.2 GB/s) to support long bursts (up to 384 flits/cycle with packed data, i.e., 3 * 8-bit data in a 32-bit wide datapath) while executing LeNet5 and MobileNetV2. AINoC supports flexible communication with many multicast/broadcast requests with non-blocking transfers. Parallel communication in AINoC can provide up to 128x more throughput (flits/cycle) and bandwidth (GB/s), using parallel routing with respect to single-path routing while executing convolution layers of LeNet5 and MobiletNetV2.

关键词： On-Chip Interconnect Network-on-Chip DNN CNN dataflow execution parallel processing

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Discriminative codeword selection for image representation

Discriminative codeword selection for image representation

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18th ACM International conference on Multimedia ACM Multimedia 2010, MM'10

作者： Zhang, Lijun Chen, Chun Bu, Jiajun Chen, Zhengguang Tan, Shulong He, Xiaofei Zhejiang Key Laboratory of Service Robot College of Computer Science Zhejiang University Hangzhou China State Key Lab. of CAD and CG College of Computer Science Zhejiang University Hangzhou China

ISBN: (纸本)9781605589336

Bag of features (BoF) representation has attracted an increasing amount of attention in large scale image processing systems. BoF representation treats images as loose collections of local invariant descriptors extracted from them. the visual codebook is generally constructed by using an unsupervised algorithm such as K-means to quantize the local descriptors into clusters. images are then represented by the frequency histograms of the codewords contained in them. To build a compact and discriminative codebook, codeword selection has become an indispensable tool. However, most of the existing codeword selection algorithms are supervised and the human labeling may be very expensive. In this paper, we consider the problem of unsupervised codeword selection, and propose a novel algorithm called Discriminative Codeword Selection (DCS). Motivated from recent studies on discriminative clustering, the central idea of our proposed algorithm is to select those codewords so that the cluster structure of the image database can be best respected. Specifically, a multi-output linear function is fitted to model the relationship between the data matrix after codeword selection and the indicator matrix. the most discriminative codewords are thus defined as those leading to minimal fitting error. Experiments on image retrieval and clustering have demonstrated the effectiveness of the proposed method. © 2010 ACM.

关键词： image retrieval

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image-Based World-perceiving Knowledge Graph (WpKG) with Imprecision 18th

Image-Based World-perceiving Knowledge Graph (WpKG) with Imp...

引用

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

作者： Rezaei, Navid Reformat, Marek Z. Yager, Ronald R. University of Alberta EdmontonT6G 1H9 Canada University of Social Sciences Lódź90-113 Poland Iona College New RochelleNY10801 United States

ISBN: (纸本)9783030501457

Knowledge graphs are a data format that enables the representation of semantics. Most of the available graphs focus on the representation of facts, their features, and relations between them. However, from the point of view of possible applications of semantically rich data formats in intelligent, real-world scenarios, there is a need for knowledge graphs that describe contextual information regarding realistic and casual relations between items in the real world. In this paper, we present a methodology of generating knowledge graphs addressing such a need. We call them World-perceiving Knowledge Graphs – WpKG. the process of their construction is based on analyzing images. We apply deep learning image processing methods to extract scene graphs. We combine these graphs, and process the obtained graph to determine importance of relations between items detected on the images. the generated WpKG is used as a basis for constructing possibility graphs. We illustrate the process and show some snippets of the generated knowledge and possibility graphs. © 2020, Springer Nature Switzerland AG.

关键词： Knowledge graph

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A Classification-Selection Approach for Self Updating of Face Verification systems Under Stringent Storage and Computational Requirements 18th

A Classification-Selection Approach for Self Updating of Fac...

引用

18th International conference on image Analysis and processing (ICIAP)

作者： Tuveri, Pierluigi Mura, Valerio Marcialis, Gian Luca Roli, Fabio Univ Cagliari Dept Elect & Elect Engn Cagliari Italy

ISBN: (纸本)9783319232348;9783319232331

Nowadays face recognition systems have many application fields. Unfortunately, lighting variations and ageing effects are still open issues. Moreover, face changes over time due to ageing. A further problem is due to occlusions, for example the glass presence. Re-enrolling user's face is time-consuming and does not solve above problems. therefore, unsupervised template update has been proposed, and named self update. Basically, this algorithm adapts/modifies templates or face models by collecting samples during system operations. the most effective variant of self update is based on the collection of multiple templates. However, this approach has been evaluated and tested in conditions under which the possible number of collectable templates is uncostrained. Actually, available resources are limited in memory and computational power, thus it is likely that it is not possible to have more than a pre-set number of templates. In this paper, we propose a classification-selection approach, based on the combination of self update and C-means algorithms, which keeps constant the number of templates and improve the ratio between intra-class variations and inter-class variations for each user. Experimental results show the effectiveness of this method with respect to standard self update.

关键词： Face recognition

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Proceedings of the 18th International conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2023

Proceedings of the 18th International Conference on Soft Com...

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Proceedings of the 18th International conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2023

ISBN: (纸本)9783031425356

the proceedings contain 61 papers. the special focus in this conference is on Soft Computing Models in Industrial and Environmental Applications. the topics include: Missing Values Imputation for Visualizing the Air Quality Evolution During the COVID-19 Pandemic in Madrid;Comparative Study of Wastewater Treatment Plant Feature Selection for COD Prediction;effectiveness of Quantum Computing in image processing for Burr Detection;hyperspectral Technology for Oil Spills Detection by Using Artificial Neural Network Classifier;Model-Based Design of the IMO-NMPC Strategy: Real-Time Implementation;first Approach of an Intelligent Automatic System for Aircraft Flap/Slat Positioning;multi-scale Neural Model for Tool-Narayanaswamy-Moynihan Model Parameter Extraction;comparative Study of Open Source Database Management systems to Enable Predictive Maintenance of Autonomous Guided Vehicles;deep Learning and Metaheuristic for Multivariate Time-Series Forecasting;forecasting Greenhouse Temperature Using Machine Learning Models: Optimizing Crop Production in Andalucia;extended Rank-Based Ant Colony Optimization Algorithm for Traveling Salesman Problem;Managing Pandemics through Agent-Based Simulation: A Case Study Based on COVID-19;leveraging Smart Meter Data for Adaptive Consumer Profiling;Categorization of CoAP DoS Attack Based on One-Class Boundary Methods;text Classification for Automatic Distribution of Review Notes in Movie Production;fault Detection in Biological Methanation Process Using Machine Learning: A Comparative Study of Different algorithms;machine Learning Approaches for Predicting Tree Growth Trends Based on Basal Area Increment;integrated Forecast and Optimization for Retailer Allocation in a Two-Echelon Inventory System;application of Fuzzy Logic to the Risk Assessment of Production Machines Failures;Neuron Characterization in Complex Cultures Using a Combined YOLO and U-Net Segmentation Approach;neuroevolutionary Transfer Learning for Time Series Forecasting;f

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Computer Aided systems theory – EUROCAST 2022 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Roberto Moreno-Díaz Franz Pichler Alexis Quesada-Arencibia

ISBN: (数字)9783031253126

ISBN: (纸本)9783031253119

this book constitutes the refereed proceedings of the 18th International conference on Computer-Aided systems theory, EUROCAST 2022, held in Las Palmas de Gran Canaria, Spain, during February 20–25, 2022. the 77 full papers included in this book were carefully reviewed and selected from 110 submissions.;they were organized in topical sections as follows: systems theory and Applications, theory and Applications of Metaheuristic algorithms, Model-Based System Design, Verification and Simulation, Applications of Signal processing Technology, Artificial Intelligence and Data Mining for Intelligent Transportation systems and Smart Mobility, Computer Vision, Machine Learning for image Analysis and Applications, Computer and systems Based Methods and Electronic Technologies in Medicine, systems in Industrial Robotics, Automation and IoT, systems thinking. Relevance for Technology, Science and Management Professionals.

关键词： Simulation and Modeling Artificial Intelligence Software Engineering/Programming and Operating systems Computer Communication Networks

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Proceedings of the 18th International conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2023

Proceedings of the 18th International Conference on Soft Com...

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Proceedings of the 18th International conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2023

ISBN: (纸本)9783031425288

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