the proceedings contain 24 papers. the topics discussed include: complex statistical models for object recognition and mass spectrometry;semi-supervised and active learning;reliable biometrical analysis in biodiversit...
ISBN:
(纸本)9789728865931
the proceedings contain 24 papers. the topics discussed include: complex statistical models for object recognition and mass spectrometry;semi-supervised and active learning;reliable biometrical analysis in biodiversity information systems;string patterns: from single clustering to ensemble methods and validation;a novel distance measure for interval data;bridging the gap between Naive Bayes and maximum entropy text classification;a weight vector feature for 3D shape matching;extending morphological signatures for visual patternrecognition;a contribution to ancient cadastral maps interpretation through colour analysis;texture learning by fractal compression;incremental non-negative matrix factorization for dynamic background modelling;and improving isometric hand gesture identification for HCI based on independent component analysis in bio-signal processing.
this paper introduces the concept of discrete multidimensional size function, a mathematical tool studying the so-called size graphs. these graphs constitutes an ingredient of Size theory, a geometrical/topological ap...
详细信息
ISBN:
(纸本)9783642208447
this paper introduces the concept of discrete multidimensional size function, a mathematical tool studying the so-called size graphs. these graphs constitutes an ingredient of Size theory, a geometrical/topological approach to shape analysis and comparison. A global method for reducing size graphs is presented, together with a theorem stating that size graphs reduced in such a way preserve all the information in terms of multidimensional size functions. this approach can lead to simplify the effective computation of discrete multidimensional size functions, as shown by examples.
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.
this paper presents an approach to derive critical points of a shape, the basis of a Reeb graph, using a combination of a medial axis skeleton and features along this skeleton. A Reeb graph captures the topology of a ...
详细信息
Tensor-basedrepresentations have been widely pursued in the last years due to the increasing number of high-dimensional datasets, which might be better described by the multilinear algebra. In this paper, we introduc...
详细信息
ISBN:
(纸本)9783319461823;9783319461816
Tensor-basedrepresentations have been widely pursued in the last years due to the increasing number of high-dimensional datasets, which might be better described by the multilinear algebra. In this paper, we introduced a recent patternrecognition technique called Optimum-Path Forest (OPF) in the context of tensor-oriented applications, as well as we evaluated its robustness to space transformations using Multilinear Principal Component Analysis in both face and human action recognition tasks considering image and video datasets. We have shown OPF can obtain more accurate recognition rates in some situations when working on tensor-oriented feature spaces.
A hurdle in the growth of model driven software engineering is our ability to evaluate the quality of models automatically. One perspective is that software quality is a function of the existence, or lack thereof, of ...
详细信息
ISBN:
(纸本)9781467370561
A hurdle in the growth of model driven software engineering is our ability to evaluate the quality of models automatically. One perspective is that software quality is a function of the existence, or lack thereof, of good and bad properties, also known as patterns and antipatterns, respectively. In this paper, we introduce the notion of using model clone detection to detect model pattern and antipattern instances by looking for models that are cross clones of pattern models. By detecting patterns at the model level, analysis is accomplished earlier in the engineering process, can be applied to primarily model-based projects, and remains at the same level of abstraction that engineers are used to. We outline the process of using model clone detection for this purpose, including representing the patterns and detection of instances. We present some Simulink examples of patternrepresentations and discuss future work and research in the area.
Relation extraction task is a crucial and challenging aspect of Natural Language Processing. Several methods have surfaced as of late, exhibiting notable performance in addressing the task;however, most of these appro...
详细信息
ISBN:
(纸本)9783031415005;9783031415012
Relation extraction task is a crucial and challenging aspect of Natural Language Processing. Several methods have surfaced as of late, exhibiting notable performance in addressing the task;however, most of these approaches rely on vast amounts of data from large-scale knowledge graphs or language models pretrained on voluminous corpora. In this paper, we hone in on the effective utilization of solely the knowledge supplied by a corpus to create a high-performing model. Our objective is to showcase that by leveraging the hierarchical structure and relational distribution of entities within a corpus without introducing external knowledge, a relation extraction model can achieve significantly enhanced performance. We therefore proposed a relation extraction approach based on the incorporation of pretrained knowledge graph embeddings at the corpus scale into the sentence-level contextual representation. We conducted a series of experiments which revealed promising and very interesting results for our proposed approach. the obtained results demonstrated an outperformance of our method compared to context-based relation extraction 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.
graphs are a powerful data structure that can be applied to several problems in bioinformatics, and efficient graph matching is often a tool required for several applications that try to extract useful information fro...
详细信息
暂无评论