標(biāo)題: Titlebook: Machine Learning in Document Analysis and Recognition; Simone Marinai,Hiromichi Fujisawa Book 2008 Springer-Verlag Berlin Heidelberg 2008 [打印本頁] 作者: 巡洋 時(shí)間: 2025-3-21 19:50
書目名稱Machine Learning in Document Analysis and Recognition影響因子(影響力)
書目名稱Machine Learning in Document Analysis and Recognition影響因子(影響力)學(xué)科排名
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書目名稱Machine Learning in Document Analysis and Recognition網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Machine Learning in Document Analysis and Recognition被引頻次
書目名稱Machine Learning in Document Analysis and Recognition被引頻次學(xué)科排名
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書目名稱Machine Learning in Document Analysis and Recognition讀者反饋
書目名稱Machine Learning in Document Analysis and Recognition讀者反饋學(xué)科排名
作者: DEMUR 時(shí)間: 2025-3-21 23:48
Book 2008th ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied作者: Relinquish 時(shí)間: 2025-3-22 00:44 作者: adequate-intake 時(shí)間: 2025-3-22 07:22
Classification and Learning Methods for Character Recognition: Advances and Remaining Problems,pplied to character recognition, with a special section devoted to the classification of large category set. We then discuss the characteristics of these methods, and discuss the remaining problems in character recognition that can be potentially solved by machine learning methods.作者: 客觀 時(shí)間: 2025-3-22 12:15 作者: maudtin 時(shí)間: 2025-3-22 13:36 作者: aerial 時(shí)間: 2025-3-22 17:24
Off-line Writer Identification and Verification Using Gaussian Mixture Models,tification and the verification task. Three types of confidence measures are defined on the scores: simple score based, cohort model based, and world model based confidence measures. Experiments demonstrate a very good performance of the system on the identification and the verification task.作者: ROOF 時(shí)間: 2025-3-22 21:35 作者: Militia 時(shí)間: 2025-3-23 05:12 作者: 江湖騙子 時(shí)間: 2025-3-23 06:59
Structure Extraction in Printed Documents Using Neural Approaches,scussed in general terms: data-driven and model-driven. In the latter, some specific approaches like rule-based or formal grammar are usually studied on very stereotyped documents providing honest results, while in the former artificial neural networks are often considered for small patterns with go作者: Aura231 時(shí)間: 2025-3-23 11:01 作者: 可商量 時(shí)間: 2025-3-23 16:03
Decision-Based Specification and Comparison of Table Recognition Algorithms,on, and comparison of recognition algorithms. We propose an approach that centers on a process-oriented description. The approach is implemented using a new scripting language called RSL (Recognition Strategy Language), which captures the recognition decisions an algorithm makes as it executes. This作者: aesthetic 時(shí)間: 2025-3-23 20:20 作者: cancellous-bone 時(shí)間: 2025-3-23 23:39 作者: fidelity 時(shí)間: 2025-3-24 05:53
Combining Classifiers with Informational Confidence,lues so that their nominal values equal the information actually conveyed. In order to do so, we assume that information depends on the actual performance of each confidence value on an evaluation set. As information measure, we use Shannon‘s well-known logarithmic notion of information. With the co作者: Mortar 時(shí)間: 2025-3-24 09:45
Self-Organizing Maps for Clustering in Document Image Analysis,of artificial neural network that computes, during the learning, an unsupervised clustering of the input data arranging the cluster centers in a lattice. After an overview of the previous applications of unsupervised learning in document image analysis, we present our recent work in the field. We de作者: 儲備 時(shí)間: 2025-3-24 12:45
Adaptive and Interactive Approaches to Document Analysis,orked applications. Context in document classification conventionally refers to language context, i.e., deterministic or statistical constraints on the sequence of letters in syllables or words, and on the sequence of words in phrases or sentences. We show how to exploit other types of statistical d作者: biosphere 時(shí)間: 2025-3-24 16:19 作者: condescend 時(shí)間: 2025-3-24 21:10 作者: Pert敏捷 時(shí)間: 2025-3-25 00:02
Learning Matching Score Dependencies for Classifier Combination,es produced by different classifiers and the dependence between scores assigned to different classes by the same classifier. Whereas the possibility of first dependence is evident, and existing classifier combination algorithms usually account for this dependence, the second type of dependence is mo作者: Anticoagulant 時(shí)間: 2025-3-25 03:44
Perturbation Models for Generating Synthetic Training Data in Handwriting Recognition,ld, the authors‘ main results regarding this research area are presented and discussed, including a perturbation model for the generation of synthetic text lines from existing cursively handwritten lines of text produced by human writers. The goal of synthetic text line generation is to improve the 作者: Adornment 時(shí)間: 2025-3-25 08:45 作者: TATE 時(shí)間: 2025-3-25 15:19
Machine Learning for Signature Verification, samples. From the viewpoint of automating the task it can be viewed as one that involves machine learning from a population of signatures. There are two types of learning tasks to be accomplished: person-independent (or general) learning and person-dependent (or special) learning. General learning 作者: Sciatica 時(shí)間: 2025-3-25 18:35 作者: Bravado 時(shí)間: 2025-3-25 23:11 作者: brother 時(shí)間: 2025-3-26 03:59 作者: 食道 時(shí)間: 2025-3-26 07:27 作者: 效果 時(shí)間: 2025-3-26 09:32
Machine Learning for Digital Document Processing: from Layout Analysis to Metadata Extraction,ssing from acquisition to indexing, from categorization to storing and retrieval..The prototypical version of the system DOMINUS is presented, whose main characteristic is the use of a Machine Learning Server, a suite of different inductive learning methods and systems, among which the more suitable作者: visceral-fat 時(shí)間: 2025-3-26 13:56
Adaptive and Interactive Approaches to Document Analysis,ncepts of unsupervised learning and adaptation. Human interaction is often more effective interspersed with algorithmic processes than only before or after the automated parts of the process. We develop a taxonomy for interaction during training and testing, and show how either human-initiated and m作者: 表被動 時(shí)間: 2025-3-26 17:46
Multiple Hypotheses Document Analysis,rs that are learned from samples in advance. The second part of the solution, which relies on a hypothesis-driven approach for the segmentation of the numerical character line will also be presented. As a test case, these solutions were applied to the Japanese postal address recognition system. They作者: 砍伐 時(shí)間: 2025-3-26 21:15 作者: GLUT 時(shí)間: 2025-3-27 01:59
Machine Learning for Signature Verification,samples are available, special learning performs better than general learning (5% higher accuracy). With special learning, verification accuracy increases with the number of samples. An interactive software implementation of signature verification involving both the learning and performance phases i作者: DEFER 時(shí)間: 2025-3-27 07:51
Book 2008ltiple techniques into an organic framework. A reader may feel that the use of machine learning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted t作者: 克制 時(shí)間: 2025-3-27 11:22 作者: STYX 時(shí)間: 2025-3-27 16:34
1860-949X ning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted t978-3-642-09511-5978-3-540-76280-5Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: Mumble 時(shí)間: 2025-3-27 18:47
Donato Malerba,Michelangelo Ceci,Margherita Berardi作者: 輕觸 時(shí)間: 2025-3-28 01:39 作者: 兇猛 時(shí)間: 2025-3-28 04:25
Sergey Tulyakov,Stefan Jaeger,Venu Govindaraju,David Doermann 作者: Flatus 時(shí)間: 2025-3-28 07:51
Sargur N. Srihari,Harish Srinivasan,Siyuan Chen,Matthew J. Beal作者: mendacity 時(shí)間: 2025-3-28 12:27 作者: jarring 時(shí)間: 2025-3-28 16:12
978-3-642-09511-5Springer-Verlag Berlin Heidelberg 2008作者: hypnotic 時(shí)間: 2025-3-28 21:30 作者: Conflict 時(shí)間: 2025-3-29 01:22
Simone Marinai,Hiromichi FujisawaPresents applications and learning algorithms for Document Image Analysis and Recognition (DIAR).Identifies good practices for the use of learning strategies in DIAR.Includes supplementary material: 作者: 友好 時(shí)間: 2025-3-29 04:39
Studies in Computational Intelligencehttp://image.papertrans.cn/m/image/620668.jpg作者: ureter 時(shí)間: 2025-3-29 07:15
Introduction to Document Analysis and Recognition,Document Analysis and Recognition (DAR) aims at the automatic extraction of information presented on paper and initially addressed to human comprehension. The desired output of DAR systems is usually in a suitable symbolic representation that can subsequently be processed by computers.作者: 怎樣才咆哮 時(shí)間: 2025-3-29 14:47 作者: 顧客 時(shí)間: 2025-3-29 18:35
e used in the diagnosis and treatment of a variety of disord.This book?provides a practically applicable guide to the latest applications of telemedicine, imaging technology and artificial intelligence (AI) in dermatology. It introduces these subjects in a clear easy-to follow format ideal for those作者: crease 時(shí)間: 2025-3-29 22:01 作者: 氣候 時(shí)間: 2025-3-30 02:26 作者: conifer 時(shí)間: 2025-3-30 07:19 作者: PAEAN 時(shí)間: 2025-3-30 11:36 作者: 機(jī)警 時(shí)間: 2025-3-30 15:37
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without Externaultaneous localisation and mapping (SLAM). Tracking semantics are established through the use of a Residual 3D U-Net and the output is fed to the SLAM algorithm. As a proof of concept, experiments are conducted on US volumes taken from a whole body fetal phantom, and from the heads of real fetuses. 作者: fulmination 時(shí)間: 2025-3-30 20:14 作者: DUCE 時(shí)間: 2025-3-30 20:55 作者: 抱怨 時(shí)間: 2025-3-31 02:49 作者: conduct 時(shí)間: 2025-3-31 07:36
