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检索条件"任意字段=10th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2021"

共 87 条记录，以下是1-10 订阅

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10th international conference on pattern recognition applications and methods, icpram 2021 and 11th international conference on pattern recognition applications and methods, icpram 2022

10th International Conference on Pattern Recognition Applica...

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10th international conference on pattern recognition applications and methods, icpram 2021 and 11th international conference on pattern recognition applications and methods, icpram 2022

ISBN: (纸本)9783031245374

the proceedings contain 8 papers. the special focus in this conference is on pattern recognition applications and methods. the topics include: Retinotopic Image Encoding by Samples of Counts;gesture recognition and Multi-modal Fusion on a New Hand Gesture Dataset;Reduced Precision Research of a GAN Image Generation Use-case;similarity Constrained Conditional Generative Auto-encoder with Generalized Dilated Networks;perusal of Camera Trap Sequences Across Locations;preface.

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icpram 2021 - Proceedings of the 10th international conference on pattern recognition applications and methods

ICPRAM 2021 - Proceedings of the 10th International Conferen...

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10th international conference on pattern recognition applications and methods, icpram 2021

ISBN: (纸本)9789897584862

the proceedings contain 74 papers. the topics discussed include: multi-level feature selection for oriented object detection;demonstrating the vulnerability of RGB-D based face recognition to GAN-generated depth-map injection;speech recognition using deep canonical correlation analysis in noisy environments;capsule networks with intersection over union loss for binary image segmentation;generalized dilation structures in convolutional neural networks;exploring motion boundaries in an end-to-end network for vision-based Parkinson’s severity assessment;converting image labels to meaningful and information-rich embeddings;exploring slow feature analysis for extracting generative latent factors;state tracking in the presence of heavy-tailed observations;and active output selection strategies for multiple learning regression models.

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pattern recognition applications and methods: 4th international conference, icpram 2015 Lisbon, Portugal, January 10–12, 2015 revised selected papers 4th

Pattern recognition applications and methods: 4th internatio...

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4th international conference on pattern recognition applications and methods, icpram 2015

作者： Fred, Ana De Marsico, Maria Figueiredo, Mário Instituto de Telecomunicações Instituto Superior Técnico University of Lisbon Lisbon Portugal Sapienza Università di Roma Rome Italy

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7th international conference on pattern recognition applications and methods, icpram 2018

7th International Conference on Pattern Recognition Applicat...

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7th international conference on pattern recognition applications and methods, icpram 2018

ISBN: (纸本)9783030054984

the proceedings contain 10 papers. the special focus in this conference is on pattern recognition applications and methods. the topics include: Interactive Design Support for Architecture Projects During Early Phases Based on Recurrent Neural Networks;CNN-Based Deep Spatial Pyramid Match Kernel for Classification of Varying Size Images;earth Mover’s Distance Between Rooted Labeled Unordered Trees Formulated from Complete Subtrees;TIMIT and NTIMIT Phone recognition Using Convolutional Neural Networks;An Efficient Hashing Algorithm for NN Problem in HD Spaces;stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals;detection and Classification of Faulty Weft threads Using Both Feature-Based and Deep Convolutional Machine Learning methods;video Activity recognition Using Sequence Kernel Based Support Vector Machines.

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Indextron 10th

Indextron

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10th international conference on pattern recognition applications and methods (icpram)

作者： Mikhailov, Alexei Karavay, Mikhail Russian Acad Sci Inst Control Problems Profsoyuznaya St 65 Moscow Russia

ISBN: (纸本)9789897584862

How to do pattern recognition without artificial neural networks, Bayesian classifiers, vector support machines and other mechanisms that are widely used for machine learning? the problem with pattern recognition machines is time and energy demanding training because lots of coefficients need to be worked out. the paper introduces an indexing model that performs training by memorizing inverse patterns mostly avoiding any calculations. the computational experiments indicate the potential of the indexing model for artificial intelligence applications and, possibly, its relevance to neurobiological studies as well.

关键词： pattern recognition Machine Learning Neural Networks Inverse Sets Inverse patterns Multidimensional Indexing

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Video Camera Identification from Sensor pattern Noise with a Constrained ConvNet 10th

Video Camera Identification from Sensor Pattern Noise with a...

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10th international conference on pattern recognition applications and methods (icpram)

作者： Timmerman, Derrick Bennabhaktula, Guru Swaroop Alegre, Enrique Azzopardi, George Univ Groningen Bernoulli Inst Math Comp Sci & Artificial Intelli Groningen Netherlands Univ Leon Grp Vis & Intelligent Syst Leon Spain

ISBN: (纸本)9789897584862

the identification of source cameras from videos, though it is a highly relevant forensic analysis topic, has been studied much less than its counterpart that uses images. In this work we propose a method to identify the source camera of a video based on camera specific noise patterns that we extract from video frames. For the extraction of noise pattern features, we propose an extended version of a constrained convolutional layer capable of processing color inputs. Our system is designed to classify individual video frames which are in turn combined by a majority vote to identify the source camera. We evaluated this approach on the benchmark VISION data set consisting of 1539 videos from 28 different cameras. To the best of our knowledge, this is the first work that addresses the challenge of video camera identification on a device level. the experiments show that our approach is very promising, achieving up to 93:1% accuracy while being robust to the WhatsApp and YouTube compression techniques. this work is part of the EU-funded project 4NSEEK focused on forensics against child sexual abuse.

关键词： Source Camera Identification Video Device Identification Video Forensics Sensor pattern Noise

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A Blended Attention-CTC Network Architecture for Amharic Text-image recognition 10th

A Blended Attention-CTC Network Architecture for Amharic Tex...

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10th international conference on pattern recognition applications and methods (icpram)

作者： Belay, Birhanu Hailu Habtegebrial, Tewodros Liwicki, Marcus Belay, Gebeyehu Stricker, Didier Tech Univ Kaiserslautern Kaiserslautern Germany Lulea Univ Technol Lulea Sweden Bahir Dar Inst Technol Bahir Dar Ethiopia DFKI Augmented Vis Dept Kaiserslautern Germany

ISBN: (纸本)9789897584862

In this paper, we propose a blended Attention-Connectionist Temporal Classification (CTC) network architecture for a unique script, Amharic, text-image recognition. Amharic is an indigenous Ethiopic script that uses 34 consonant characters with their 7 vowel variants of each and 50 labialized characters which are derived, with a small change, from the 34 consonant characters. the change involves modifying the structure of these characters by adding a straight line, or shortening and/or elongating one of its main legs including the addition of small diacritics to the right, left, top or bottom of the character. Such a small change affects orthographic identities of character and results in shape similarly among characters which are interesting, but challenging task, for OCR research. Motivated with the recent success of attention mechanism on neural machine translation tasks, we propose an attention-based CTC approach which is designed by blending attention mechanism directly within the CTC network. the proposed model consists of an encoder module, attention module and transcription module in a unified framework. the efficacy of the proposed model on the Amharic language shows that attention mechanism allows learning powerful representations by integrating information from different time steps. Our method outperforms state-of-the-art methods and achieves 1.04% and 0.93% of the character error rate on ADOCR test datasets.

关键词： Amharic Script Blended Attention-CTC BLSTM CNN Encoder-decoder Network Architecture OCR pattern recognition

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pattern recognition applications and methods 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Maria De Marsico Gabriella Sanniti di Baja Ana Fred

ISBN: (数字)9783031245381

ISBN: (纸本)9783031245374

this book contains revised and extended versions of selected papers from the 10th and 11;international conference on pattern recognition, icpram 2021 and 2022, held in February 2021 and 2022. Due to COVID-19 pandemic the conferences were held virtually. Both conferences received in total 204 submissions from which 8 full papers were carefully reviewed and selected for presentation in this volume. the papers span a wide range of investigation as well as development lines, which of course always reflect the last trends of research in the pattern recognition community.

关键词： pattern recognition Machine Learning Computer Systems Organization and Communication Networks Computer applications Information Systems and Communication Service

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A Wideband Rectangular Microstrip Patch Antenna with Partial Ground Plane for 5G applications 10

A Wideband Rectangular Microstrip Patch Antenna with Partial...

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Joint 10th international conference on Informatics, Electronics and Vision, ICIEV 2021 and 2021 5th international conference on Imaging, Vision and pattern recognition, icIVPR 2021

作者： Paul, Liton Chandra Ali, Md Hossain Sarker, Nayan Mahmud, Md Zulfiker Azim, Rezaul Islam, Mohammad Tariqul Dept. of EECE Pabna University of Science and Technology Pabna Bangladesh Dept. of EEE Bangladesh University of Business and Technology Dhaka Bangladesh Dept. of CSE Jagannath University Bangladesh Dept. of Physics University of Chittagong Chittagong Bangladesh Dept. of EESE Universiti Kebangsaan Malaysia Malaysia

ISBN: (纸本)9781665449212

A directional wideband microstrip line fed rectangular patch antenna has been proposed for the 28 GHz 5G applications. Initially, a conventional rectangular microstrip patch antenna has been designed thereafter to enhance the performances as well as to tune in the desired operating frequency range (24 GHz-30 GHz) a cutting edge with partial ground plane technique is used. At the intermediate stage, a star-shaped parasitic element has been used for the gain enhancement of the antenna. However, the high gain of the antenna is retained by optimizing the dimensions and position of the cutting edge as well as the ground plane without introducing any parasitic element on the patch which is the simplicity of the proposed antenna. the proposed antenna operates at the 28.201 GHz band ranging from 26.984 GHz to 29.551 GHz. It has an average radiation efficiency of 84.5%. As the proposed antenna possesses a smaller size (20 × 17 × 1.575 mm3) and wide bandwidth of 2.567 GHz with a high gain and directivity over the entire operating band, it can be considered as a potential candidate for the 28 GHz millimetre wave (mm-wave) applications. Contribution- A single element rectangular microstrip patch antenna (RMPA) having a bandwidth of 2.567 GHz has been designed for the 28 GHz 5G applications. © 2021 IEEE

关键词： Microstrip antennas

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2021 Joint 10th international conference on Informatics, Electronics and Vision, ICIEV 2021 and 2021 5th international conference on Imaging, Vision and pattern recognition, icIVPR 2021

2021 Joint 10th International Conference on Informatics, Ele...

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Joint 10th international conference on Informatics, Electronics and Vision, ICIEV 2021 and 2021 5th international conference on Imaging, Vision and pattern recognition, icIVPR 2021

ISBN: (纸本)9781665449212

the proceedings contain 44 papers. the topics discussed include: a wideband rectangular microstrip patch antenna with partial ground plane for 5g applications;development of a Bangla speech to text conversion system using deep learning;automatic identification of mice social behavior through multi-modal latent space clustering;a deep learning approach for Bangla image captioning system;semantic representation of sentences employing an automated threshold;a deep learning approach for Bangla speech to text conversion;a systematic review on the chronological development of Bangla sign language recognition systems;static output feedback stabilizing control for Takagi-Sugeno fuzzy systems;improved transfer learning architecture to classify covid-19 affected chest x-rays using noisy student pre-training;human action recognition based on a sequential deep learning model;and a vision-based lane detection approach for autonomous vehicles using a convolutional neural network architecture.

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