An impact of an asteroid on planet Earth could have catastrophic consequences. To eliminate this threat, the first step that needs to be done is to identify in advance all the asteroids near Earth. In this paper, we p...
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the Modulation Transfer Function (MTF) and the Noise Power Spectrum (NPS) characterize imaging system sharpness/resolution and noise, respectively. Both measures are based on linear system theory. However, they are ap...
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By a car license plate recognition, we mean a software system processingimages and providing an alphanumeric transcription of car plates included in an image. We divide the task into four sub-tasks: license plate loc...
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ISBN:
(纸本)9781509049189
By a car license plate recognition, we mean a software system processingimages and providing an alphanumeric transcription of car plates included in an image. We divide the task into four sub-tasks: license plate localization, license plate extraction, characters segmentation and characters recognition. All four sub-tasks are discussed in the context of standard approaches and own solution based on a chain of standard and soft computing imageprocessingalgorithms is presented. In this chain, the F-transform approximate pattern matching algorithm plays the crucial role. For the solution, we presented recognition ability for a dataset which includes 500 images with difficult conditions.
Haze is an atmospheric phenomenon that fogs the visibility of the scenes. Removing the haze has been an important issue in imageprocessing technologies. Many image dehazing technologies with evolution algorithms have...
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Haze is an atmospheric phenomenon that fogs the visibility of the scenes. Removing the haze has been an important issue in imageprocessing technologies. Many image dehazing technologies with evolution algorithms have been proposed to remove the fog in the image. However, these algorithms usually are compute-intensive. In this paper, we propose a parallel hybrid evolution algorithm based on GPU to enhance the computational performance. In traditional evolution algorithms, the calculation of fitness function occupies the most of the computation time. In the proposed method, we implement this part on GPU by using CUDA framework to reduce the computational load. the experiment results show that the proposed method can remove the haze efficiently and successfully.
the edge-directed interpolation scheme is a non-iterative, orientation-adaptive method to enhance image resolution with better visual effect than conventional interpolation methods. It interpolates the missing pixels ...
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the edge-directed interpolation scheme is a non-iterative, orientation-adaptive method to enhance image resolution with better visual effect than conventional interpolation methods. It interpolates the missing pixels based on the covariance of a high-resolution image estimated from the covariance of the low-resolution image. In spite of the impressive performance, the computational complexity of covariance-based adaptation is significantly higher than that of the conventional linear interpolation algorithms. In this paper, we propose a GPU-based massively parallel version of the edge-directed interpolation scheme. A speedup of 61.7x can be achieved with respect to its single-threaded CPU counterpart in the host computer.
this book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision: algorithms for Big Data, MCV 2014, held in Cambridge, MA, USA, in September 2019, in co...
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ISBN:
(数字)9783319139722
ISBN:
(纸本)9783319139715
this book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision: algorithms for Big Data, MCV 2014, held in Cambridge, MA, USA, in September 2019, in conjunction withthe 17th International conference on Medical image Computing and Computer-Assisted Intervention, MICCAI 2014. the one-day workshop aimed at exploring the use of modern computer vision technology and "big data" algorithms in tasks such as automatic segmentation and registration, localization of anatomical features and detection of anomalies emphasizing questions of harvesting, organizing and learning from large-scale medical imaging data sets and general-purpose automatic understanding of medical images. the 18 full and 1 short papers presented in this volume were carefully reviewed and selected from 30 submission.
this three-volume set CCIS2493–2495constitutes the refereed proceedings of the 17th Asian conference on Recent Challenges in Intelligent Information and Database systems, ACIIDS 2025, held in Kitakyushu, Japan, durin...
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ISBN:
(数字)9789819658817
ISBN:
(纸本)9789819658800
this three-volume set CCIS
2493
–
2495
constitutes the refereed proceedings of the 17th Asian conference on Recent Challenges in Intelligent Information and Database systems, ACIIDS 2025, held in Kitakyushu, Japan, during April 23-25, 2025.
the 80 papers included in these proceedings were carefully reviewed and selected from 301 submissions. the papers are organized in the following topical sections:
Volume I: Data Analysis and Signal processing; Development and Application of Large Language Models; Speech and Natural Language processing.
Volume II: Artificial Intelligence in Multimedia Technologies; image and Video processing.
Volume III: Machine Learning and Artificial Intelligence Applications; Intelligent Information systems and Advanced Problem-Solving algorithms.
A trajectory building based on a camera data is one of the most popular tasks in the field of machine vision. In particular, this task appears when it is necessary to navigate in the absence of signals from global nav...
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this two-volume proceedings, LNAI 15683 and LNAI 15684, constitutes the proceedings of the 17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025, held in Kitakyushu, Japan, during Apr...
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ISBN:
(数字)9789819660087
ISBN:
(纸本)9789819660070
this two-volume proceedings, LNAI 15683 and LNAI 15684, constitutes the proceedings of the 17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025, held in Kitakyushu, Japan, during April 23-25, 2025.
the 56 full papers and presented in these two volumes were carefully reviewed and selected from 301 submissions.
the papers are organized in the following topical sections:
Part I: Data Mining, processing and Integration; Deep Learning Methods and Applications; Generative Models Applications; Intelligent Information systems and Problem-Solving algorithms.
Part II: Games and Decision theories; imageprocessing and Computer Vision; Intelligent Techniques in Optimization; Machine Learning Techniques and Applications.
this two-volume proceedings, LNAI 15683 and LNAI 15684, constitutes the proceedings of the 17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025, held in Kitakyushu, Japan, during Apr...
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ISBN:
(数字)9789819660056
ISBN:
(纸本)9789819660049
this two-volume proceedings, LNAI 15683 and LNAI 15684, constitutes the proceedings of the 17th Asian conference on Intelligent Information and Database systems, ACIIDS 2025, held in Kitakyushu, Japan, during April 23-25, 2025.
the 56 full papers and presented in these two volumes were carefully reviewed and selected from 301 submissions.
the papers are organized in the following topical sections:
Part I: Data Mining, processing and Integration; Deep Learning Methods and Applications; Generative Models Applications; Intelligent Information systems and Problem-Solving algorithms.
Part II: Games and Decision theories; imageprocessing and Computer Vision; Intelligent Techniques in Optimization; Machine Learning Techniques and Applications.
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