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检索条件"任意字段=12th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2023"

共 89 条记录，以下是51-60 订阅

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Advances in Computational Intelligence 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Ignacio Rojas Gonzalo Joya Joan Cabestany

ISBN: (数字)9783642386824

ISBN: (纸本)9783642386817

this two-volume set LNCS 7902 and 7903 constitutes the refereed proceedings of the 12th international Work-conference on Artificial Neural Networks, IWANN 2013, held in Puerto de la Cruz, Tenerife, Spain, in June 2013. the 116 revised papers were carefully reviewed and selected from numerous submissions for presentation in two volumes. the papers explore sections on mathematical and theoretical methods in computational intelligence, neurocomputational formulations, learning and adaptation emulation of cognitive functions, bio-inspired systems and neuro-engineering, advanced topics in computational intelligence and applications.

关键词： Computational Biology/Bioinformatics pattern recognition Artificial Intelligence Data Mining and Knowledge Discovery Models and Principles Bioinformatics

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Advances in Computational Intelligence 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Ignacio Rojas Gonzalo Joya Joan Gabestany

ISBN: (数字)9783642386794

ISBN: (纸本)9783642386787

关键词： Computational Biology/Bioinformatics pattern recognition Artificial Intelligence Data Mining and Knowledge Discovery Models and Principles Bioinformatics

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Proceedings of the Satellite Workshops of ICVGIP 2021 1

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丛书名： Lecture Notes in Electrical Engineering

1000年

作者： Uma Mudenagudi Aditya Nigam Ravi Kiran Sarvadevabhatla Ayesha Choudhary

ISBN: (数字)9789811941368

ISBN: (纸本)9789811941351;9789811941382

this book constitutes peer-reviewed proceedings of satellite workshops of the 12th Indian conference on Computer Vision, Graphics, and Image Processing (ICVGIP 2021). the book focuses on medical image processing, digital heritage, document analysis and recognition, and computer vision applications. the first part includes submissions on digital archiving and restoration methods with interesting and innovative research components. the second part focuses on medical imaging modalities including MRI, X-ray, CT, imaging in nuclear medicine, medical ultrasound, optical and confocal microscopy, and video and range data images. the third part deals with document analysis and recognition and focuses on text recognition, document layout analysis, understanding, historical and degraded document analysis, datasets, performance evaluation, metrics, etc. the fourth part of this book includes research work from academia and industry across the globe on smart, innovative, and practical applications of computer vision for industrial and societal impact. this book shares innovative ideas, experience and expertise, and ongoing research ideas and will be helpful for researchers and practitioners in academia and industry.

关键词： Signal, Image and Speech Processing Computer Imaging, Vision, pattern recognition and Graphics Data Structures and Information theory Artificial Intelligence

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Bird-Like Information Processing for AI-Based pattern recognition

Bird-Like Information Processing for AI-Based Pattern Recogn...

引用

Mexican international conference on Artificial Intelligence

作者： Tuan D. Pham Aizu Research Cluster for Medical Engineering and Informatics Center for Advanced Information Science and Technology The University of Aizu

ISBN: (纸本)9781479926060

Artificial-intelligence (AI)-base pattern recognition is of particular interests to many scientific disciplines ranging from life science to engineering. Practical applications of pattern or object recognition methods are numerous but still encountering many problems including the inherent difficulty in computerized feature extraction and classification. this paper proposes a strategy for object recognition resembling the active template matching strategy in birds. Experimental results on several databases suggest that using the active vision processing can improve classification rates implemented with various classifiers.

关键词： Bird-like information processing Active vision AI-based pattern recognition

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Determining local natural scales of curves

Determining local natural scales of curves

引用

international conference on pattern recognition

作者： P.L. Rosin Institute for Remote Sensing Applications Joint Research Centre Varese Italy

An alternative to representing curves at a single scale or a fixed number of multiple scales is to represent them only at their natural (i.e. most significant) scales. this allows all the important information concerning the different sized structures contained in the curve to be explicitly represented without the overhead of redundant representations of the curve. this paper describes several approaches to determining the local natural scales of curves. that is, various possibly overlapping sections of the curve should be represented at certain scales depending on their shape. the merits and drawbacks of the techniques are described, and the results of implementing one of them are shown.

关键词： Robustness Sampling methods Remote sensing Head Shape Computer vision Image segmentation Quantization Costs Statistics

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Stabilizing linear prediction models using autoencoder 12th

Stabilizing linear prediction models using autoencoder

引用

12th international conference on Advanced Data Mining and applications, ADMA 2016

作者： Gopakumar, Shivapratap Tran, Truyen Phung, Dinh Venkatesh, Svetha Center for Pattern Recognition and Data Analytics Deakin University Burwood Australia

ISBN: (纸本)9783319495859

To date, the instability of prognostic predictors in a sparse high dimensional model, which hinders their clinical adoption, has received little attention. Stable prediction is often overlooked in favour of performance. Yet, stability prevails as key when adopting models in critical areas as healthcare. Our study proposes a stabilization scheme by detecting higher order feature correlations. Using a linear model as basis for prediction, we achieve feature stability by regularizing latent correlation in features. Latent higher order correlation among features is modelled using an autoencoder network. Stability is enhanced by combining a recent technique that uses a feature graph, and augmenting external unlabelled data for training the autoencoder network. Our experiments are conducted on a heart failure cohort from an Australian hospital. Stability was measured using Consistency index for feature subsets and signal-to-noise ratio for model parameters. Our methods demonstrated significant improvement in feature stability and model estimation stability when compared to baselines. © Springer international Publishing AG 2016.

关键词： Stability

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Fast Retrieval Method of English Translation Corpus Based on Top-k Query Algorithm 12th

Fast Retrieval Method of English Translation Corpus Based on...

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12th international conference on Frontier Computing, FC 2022

作者： Qin, Lihui International Business Department Dongfang College Shandong University of Finance and Economics Shandong Taian271000 China

ISBN: (纸本)9789819914272

the fast retrieval method of English translation corpus based on Top-k query algorithm is a technology to retrieve the most commonly used words in English translation corpus. the top k query algorithm uses the first k most commonly used words to retrieve all other words in the text, and then returns them to the user. this technique uses it to find out which word in the Chinese translation corpus is more commonly used than other words. the fast retrieval method of English translation corpus is a kind of machine translation, which uses statistical technology to obtain high-quality results at low computational cost. It is the most commonly used method to translate text into another language, and is widely used in many applications, such as automatic speech recognition (ASR) system, web search engine and so on. Compared with other methods, the main advantage of this technology is that it can process very large data sets without significant quality loss. Since then, this method has been widely used and studied by many researchers in various fields such as computer science, linguistics, information retrieval and natural language processing. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Information retrieval

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DoppelSearch: A Novel Approach to Content-Based Video Retrieval for AI Challenge HCMC 2023 23

DoppelSearch: A Novel Approach to Content-Based Video Retrie...

引用

12th international Symposium on Information and Communication Technology, SOICT 2023

作者： Phan Nguyen Huu, Phong Tran Dinh, Khoa Tran Kim Ngoc, Ngan Tran Duc, Luong Le Hoang, Phuc Nguyen Huu, Quyen Phan the, Duy Pham, Van-Hau Information Security Laboratory University of Information Technology Vietnam National University Ho Chi Minh City Ho Chi Minh city Viet Nam Faculty of Information Science and Engineering University of Information Technology Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Ho Chi Minh city Viet Nam

ISBN: (纸本)9798400708916

Video retrieval, which has been considered as a critical task in the field of computer vision and pattern recognition recently, finds extensive applications in several aspects such as education, entertainment, security, and healthcare. However, it faces challenges due to the complexity of video data, the instability in feature extraction methods, or the semantic disparities between videos and text. In this paper, we present a novel approach for content-based video retrieval, named DoppelSearch, leveraging the CLIP (Contrastive Language-Image Pre-training) model architecture to classify and label video segments, offering users the ability to search for videos based on specific content. Our method capitalizes on the ViT-b/32 model for feature extraction and employs feature embedding, in conjunction with the Faiss library, to enhance search efficiency. Experimental results demonstrate our model's high accuracy and swift retrieval times, promising new opportunities in content-based video retrieval for researchers, developers, and end-users. this paper not only introduces the application of the CLIP and ViT-b/32 models, but also elaborates on the specific feature extraction process and the utilization of Faiss for optimizing video retrieval. the DoppelSearch method represents a significant stride in the field of video retrieval and holds promise for diverse applications across various industries. © 2023 ACM.

关键词： Feature extraction

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Semi-supervised polarimetric SAR images classification based on FixMatch 12

Semi-supervised polarimetric SAR images classification based...

引用

SPIE 12th international Symposium on Multispectral Image Processing and pattern recognition, MIPPR 2023

作者： Lv, Qiwen Wang, Lei Hong, Hanyu Zhao, Shuwei Peng, Lingmu Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology 206 Guanggu 1st Road East Lake New Technology Development ZoneHubei Province Wuhan City430000 China

ISBN: (数字)9781510674929

ISBN: (纸本)9781510674912

Polarimetric synthetic aperture radar (PolSAR) images are widely used in the fields of disaster detection and military reconnaissance. PolSAR image classification is one of the most important applications in PolSAR image interpretation. Existing image classification methods based on deep learning usually rely on a large number of labeled training data. Labeling large-scale data sets is expensive and time-consuming therefore, semi-supervised learning is an important research direction in the field of image classification. Fixmath has achieved excellent semi-supervised classification performance for nature image, so it is introduced into the field of PolSAR image interpretation, and to improve the performance of semi-supervised PolSAR image classification. Fixmatch has the following advantages: (1) It extends the training data, using generated, labeled and unlabeled data to train the network. (2) By utilizing the information of unlabeled data, FixMatch can improve the generalization ability of the classification model, thus allowing the model to better predict on unseen data. Because of these two advantages, FixMatch has shown excellent results in semi-supervised PolSAR image classification. Experiments on two real PolSAR datasets show that the overall accuracy reaches 89.9 % when the number of labeled samples is set to 110, and reaches 98.6 % when the number of labeled samples is set to 1000. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image classification

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pattern recognition with spiking neural networks

Pattern recognition with spiking neural networks

引用

12th Mexican international conference on Artificial Intelligence, MICAI 2013

作者： Paz, Israel Tabarez Gress, Neil Hernańdez Mendoza, Miguel Gonzaĺez Universidad Autónoma del Estado de México Blvd. Universitario s/n Predio San Javier Atizapán de Zaragoza Mexico Tecnológico de Monterrey Campus Estado de México Carr. L. de Guadalupe km 3.5 Col. Margarita Maza de Juarez Atizapán de Zaragora Mexico

ISBN: (纸本)9783642451102

this manuscript is focused on some applications of method Spikeprop of Spiking Neural Networks (SNN) using an especific hardware for parallel programming in order to measure the eficience. So, we are interested on pattern recognition and clustering, that are the main problems to solve for Artificial Neural Networks (ANN). As a result, we are going to know the considerations,its limitations and advantages, that we have to take into account for applying SNN. the main advantage is that the quantity of applications can be expanded for real applications linear or non linear, with more than one attribute, and big volume of datas. In contrast, other methods spend a lot of memory to process the information, which computational complexity is propotional to the volume and quantity of attributes of datas, also is more difficult to program the algorithm for multiclass database. However, the main limitation of SNN is the convergence, that tends forward a Local minimum Value. this implies a high dependency on the configuration and proposed architecture. On the other hand, we programmed the algorithm of SNN in a GPU model NVIDIA GeForce 9400 M. In this GPU we had to reduce parallelism in order to increase quantity of layers and neurons in the same hardware in spite of contains 60000 threads, they were not enought. On the otrher hand, the divergence is reduced when the database is bigger for database multiclass. © Springer-Verlag 2013.

关键词： Neural networks

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