the proceedings contain 42 papers from the MIR'04 - Proceedings of the 6th ACM SIGMM internationalworkshop on Multimedia Information Retrieval. the topics discussed include: an user preference information based k...
详细信息
ISBN:
(纸本)1581139403
the proceedings contain 42 papers from the MIR'04 - Proceedings of the 6th ACM SIGMM internationalworkshop on Multimedia Information Retrieval. the topics discussed include: an user preference information based kernel for SVM active learning in content-based image retrieval;retrieval of difficult image classes using SVM-based relevance feedback;boosting contextual information in content-based image retrieval;content based access for a massive database of human observation video;structuring home video by snippet detection and pattern parsing;repeating pattern discovery and structure analysis from acoustic music data;high performance crawling system;and image recognition for digital libraries.
this book constitutes the refereed proceedings of the 11th IAPR-TC-15 internationalworkshop on graph-based Representation in patternrecognition, GbRPR 2017, held in Anacapri, Italy, in May 2017. the 25 full papers a...
详细信息
ISBN:
(数字)9783319589619
ISBN:
(纸本)9783319589602
this book constitutes the refereed proceedings of the 11th IAPR-TC-15 internationalworkshop on graph-based Representation in patternrecognition, GbRPR 2017, held in Anacapri, Italy, in May 2017. the 25 full papers and 2 abstracts of invited papers presented in this volume were carefully reviewed and selected from 31 submissions. the papers discuss research results and applications in the intersection of patternrecognition, image analysis, graphtheory, and also the application of graphs to patternrecognition problems in other fields like computational topology, graphic recognition systems and bioinformatics.
Our work is focused on the automatic categorization of medical images according to their visual content for indexing and retrieval purposes in the context of the CISMeF health-catalogue. the aim of this study is to as...
详细信息
ISBN:
(纸本)9728865554
Our work is focused on the automatic categorization of medical images according to their visual content for indexing and retrieval purposes in the context of the CISMeF health-catalogue. the aim of this study is to assess the performance of our medical image categorization algorithm according to the image's modality, anatomic region and view angle. For this purpose we represented the medical images using texture and statistical features. the high dimensionality led us to transform this representation into a symbolic description, using block labels obtained after a clustering procedure. A medical image database of 10322 images, representing 33 classes was selected by an experienced radiologist. the classes are defined considering the images medical modality, anatomical region and acquisition view angle. An average precision of approximately 83% was obtained using k-NN classifiers, and a top performance of 91.19% was attained with 1-NN when categorizing the images with respect to the defined 33 classes. the performances raise to 93.62% classification accuracy when only the modality is needed. the experiments we present in this paper show that the considered image representation obtains high recognition rates, despite the difficult context of medical imaging.
three-dimensional geometric data offer an excellent domain for studying representation learning and generative modeling. In this paper, we look at geometric data represented as point clouds. We introduce a deep autoen...
详细信息
Representation learning is one of the foundations of Deep Learning and allowed important improvements on several Machine Learning tasks, such as Neural Machine Translation, Question Answering and Speech recognition. R...
详细信息
A concept relating story-board description of video sequences with spatio-temporal hierarchies build by local contraction processes of spatio-temporal relations is presented. Object trajectories are curves in which th...
详细信息
In the last few years, energy efficiency has become a research field of high interest for governments and industry. In order to understand consumption data and provide useful information for high-level decision making...
详细信息
ISBN:
(纸本)9789897582226
In the last few years, energy efficiency has become a research field of high interest for governments and industry. In order to understand consumption data and provide useful information for high-level decision making processes in energy efficiency, there is the problem of information modelling and knowledge discovery coming from a set of energy consumption sensors. this paper focuses in this problem, and explores the use of symbolic regression techniques able to find out patterns in data that can be used to extract an analytical formula that explains the behaviour of energy consumption in a set of public buildings. More specifically, we test the feasibility of different representations such as trees and straight line programs for the implementation of genetic programming algorithms, to find out if a building consumption data can be suitably explained from the energy consumption data from other similar buildings. Our experimental study suggests that the Straight Line Programs representation may overcome the limitations of traditional tree-basedrepresentations and provides accurate patterns of energy consumption models.
Arbitrary shape text detection is still an open problem due to several challenges, e.g., dense text adhesion, various sizes, and noises. In this work, we propose a novel scene text detection network by extracting and ...
详细信息
ISBN:
(数字)9781665490627
ISBN:
(纸本)9781665490627
Arbitrary shape text detection is still an open problem due to several challenges, e.g., dense text adhesion, various sizes, and noises. In this work, we propose a novel scene text detection network by extracting and connecting a set of points on the boundary of each text instance. Our method mainly consists of three branches, including text center line (TCL) prediction, text orientation (TO) prediction, and text boundary offset (TBO) prediction to get the text boundary point proposals. Utilize these proposals, and the final refinement results can be obtained by point sampling and graph attention network(GAT). the detector can overcome the text instance sticking problem withthese text boundary representations. Additionally, we propose distance-based dice loss and instance-aware L1 loss to remove false positives and get over various text sizes on text boundary offset prediction respectively. In this way, our method can directly and efficiently generate accurate text boundaries without any post-processing. Extensive experiments on publicly available datasets show the effectiveness of our design and training strategy, which also demonstrates our method's state-of-the-art performance for arbitrary shape text detection.
Gender recognition in videos is a challenging task that has received limited attention in recent years. To tackle this problem, we propose to explore the use of intermediate features of a Convolutional Neural Network ...
详细信息
ISBN:
(纸本)9783030011321;9783030011314
Gender recognition in videos is a challenging task that has received limited attention in recent years. To tackle this problem, we propose to explore the use of intermediate features of a Convolutional Neural Network (CNN) with a component-based face representation methodology. Withthis approach we intend to exploit the gender information provided by different face parts. the features extracted from video key frames are combined with two different strategies to preserve the temporal information, and Random Forest classifiers are employed to obtain a final gender prediction for a video sequence. Our results on the McGill and COX datasets show that our proposal outperforms the end-to-end CNN approach and, in the McGill dataset, 100% of accuracy was obtained.
the proceedings contain 20 papers. the special focus in this conference is on Biometrics, Document Image Inspection and Applications. the topics include: Voice passphrase variability evaluation for speaker recognition...
ISBN:
(纸本)9783319201245
the proceedings contain 20 papers. the special focus in this conference is on Biometrics, Document Image Inspection and Applications. the topics include: Voice passphrase variability evaluation for speaker recognition;studies in individuality;robust 2d face recognition under different illuminations using binarized partial face features;comparison of multidirectional representations for multispectral palmprint recognition;efficient iris recognition system using relational measures;a study of identification performance of facial regions from CCTV images;inverse of low resolution line halftone images for document inspection;when document security brings new challenges to document analysis;stamp verification for automated document authentication;introducing and analysis of the windows 8 event log for forensic purposes;automatic creation of computer forensic test images;art forgery detection via craquelure pattern matching;forensics acquisition and analysis of instant messaging and VOIP applications and an integrated tool for forensic writer identification.
暂无评论