書目名稱Artificial Neural Networks in Pattern Recognition影響因子(影響力)學科排名
書目名稱Artificial Neural Networks in Pattern Recognition網(wǎng)絡(luò)公開度
書目名稱Artificial Neural Networks in Pattern Recognition網(wǎng)絡(luò)公開度學科排名
書目名稱Artificial Neural Networks in Pattern Recognition被引頻次
書目名稱Artificial Neural Networks in Pattern Recognition被引頻次學科排名
書目名稱Artificial Neural Networks in Pattern Recognition年度引用
書目名稱Artificial Neural Networks in Pattern Recognition年度引用學科排名
書目名稱Artificial Neural Networks in Pattern Recognition讀者反饋
書目名稱Artificial Neural Networks in Pattern Recognition讀者反饋學科排名
作者: Bumble 時間: 2025-3-21 20:34
Analyzing Dynamic Ensemble Selection Techniques Using Dissimilarity Analysisiques was proposed by the authors and uses meta-learning to define the competence of base classifiers based on different criteria. In the dissimilarity analysis, this proposed technique appears closer to the Oracle when compared to others, which would seem to indicate that using different bits of in作者: Fallibility 時間: 2025-3-22 02:15 作者: Figate 時間: 2025-3-22 08:26
Combining Bipartite Graph Matching and Beam Search for Graph Edit Distance Approximationork with a fast tree search procedure. More precisely, we regard the assignment from the original approximation as a starting point for a subsequent beam search. In an experimental evaluation on three real world data sets a substantial gain of assignment accuracy can be observed while the run time r作者: semble 時間: 2025-3-22 10:51 作者: 痛恨 時間: 2025-3-22 16:06
Part-Based High Accuracy Recognition of Serial Numbers in Bank Notesconducted on a RMB serial number character database show that the test accuracy boosted from 98.90% to 99.33% by utilizing the proposed method with multiple voting based combination strategy. The part-based recognition method can also be extended to other types of banknotes, such as Euro, U.S. and C作者: 繁榮地區(qū) 時間: 2025-3-22 17:07
,“Animal Models” for Fetal Alcohol Effects,al properties of the required input-output mapping using the minimum number of hidden nodes. Hidden nodes with least contribution to the error minimization at the output layer will be pruned. Experimental results show that the proposed pruning algorithm correctly prunes irrelevant hidden units.作者: 激勵 時間: 2025-3-22 21:22
Leo R. Leader MD, FRACOG, FRCOG, FCOG (SA)iques was proposed by the authors and uses meta-learning to define the competence of base classifiers based on different criteria. In the dissimilarity analysis, this proposed technique appears closer to the Oracle when compared to others, which would seem to indicate that using different bits of in作者: Progesterone 時間: 2025-3-23 01:56
Effect of genome on size at birthg to the resemblance to the underlying concept distribution. Simulation produced with synthetic problems indicate that the proposed fusion technique is able to increase system performance when input data streams incorporate abrupt concept changes, yet maintains a level of performance that is compara作者: Interferons 時間: 2025-3-23 09:16 作者: 國家明智 時間: 2025-3-23 11:15
F. Sharp,R. B. Fraser,R. D. B. Milners concept class share the common property of being invariant against global additive effects. We give a theoretical characterization of contrast classifiers and analyze the effects of replacing general linear classifiers by these new models in standard training algorithms.作者: Fresco 時間: 2025-3-23 15:10 作者: 不能仁慈 時間: 2025-3-23 21:24 作者: Emg827 時間: 2025-3-24 01:31 作者: AORTA 時間: 2025-3-24 03:38
Trisha Vigneswaran,John Simpsonformation extraction systems. Active learning has been proven to be effective in reducing manual annotation efforts for supervised learning tasks where a human judge is asked to annotate the most informative examples with respect to a given model. However, in most cases reliable human judges are not作者: 混合 時間: 2025-3-24 09:04
John Simpson,Vita Zidere,Owen I. Millerthe discrete recognition rate. This leads to inferior feature selection results. To solve this problem, we propose using a least squares support vector regressor (LS SVR), instead of an LS support vector machine (LS SVM). We consider the labels (1/-1) as the targets of the LS SVR and the mean absolu作者: sphincter 時間: 2025-3-24 13:08
Nadja Reissland,Barbara S. Kisilevskyle to the use of many methods, including Neural Network methods, for solving these tasks. To avoid these phenomena, various Representation learning algorithms are used, as a first key step in solutions of these tasks, to transform the original high-dimensional data into their lower-dimensional repre作者: 柔美流暢 時間: 2025-3-24 17:38 作者: 奇怪 時間: 2025-3-24 21:51
Robert Lickliter PhD,Lorraine E. Bahrick PhDonal data modeling has been seldom mentioned in the literature. However, proportional data are a common way of representing large data in a compact fashion and often arise in pattern recognition applications frameworks. HMMs have been first developed for discrete and Gaussian data and their extensio作者: 歡騰 時間: 2025-3-24 23:33
Leo R. Leader MD, FRACOG, FRCOG, FCOG (SA)iption to the minority class but in contrast to many other algorithms, awareness of samples of the majority class is used to improve the estimation process. The majority samples are incorporated in the optimization procedure and the resulting domain descriptions are generally superior to those witho作者: GROG 時間: 2025-3-25 06:51
Robert Lickliter PhD,Lorraine E. Bahrick PhDion of useful data. In this work we propose a multiple-imputation-type framework for estimating the missing values of a time series. This framework is based on iterative and successive forward and backward forecasting of the missing values, and constructing ensembles of these forecasts. The iterativ作者: TAG 時間: 2025-3-25 10:49 作者: Fierce 時間: 2025-3-25 12:55 作者: 為現(xiàn)場 時間: 2025-3-25 15:51 作者: 災(zāi)難 時間: 2025-3-25 23:28
F. Sharp,R. B. Fraser,R. D. B. Milner. Such objectives might be the induction of a large margin or the reduction of the number of involved features. The underlying concept class of linear classifiers is analyzed less frequently. It is implicitly assumed that all classifiers of this function class share the same common properties..In th作者: 雪上輕舟飛過 時間: 2025-3-26 00:20
https://doi.org/10.1007/978-3-030-00051-6the property to benefit from fuzzy labeled data in the training phase and can determine fuzzy memberships for input data. The algorithm can be considered as an extension of the traditional multi-class SVM for crisp labeled data, and it also extents the fuzzy SVM approach for fuzzy labeled training d作者: 共同確定為確 時間: 2025-3-26 06:13 作者: 石墨 時間: 2025-3-26 08:55
E. Kastendieck,W. Künzel,A. Jensenn-site preferences is critically important in functional genomics and gene therapy studies. It has been found that the deformability property of the local DNA structure of the integration sites, called .., is of significant importance in the target-site selection process. We considered the .. profil作者: 滲入 時間: 2025-3-26 15:10 作者: 敬禮 時間: 2025-3-26 19:34 作者: JOG 時間: 2025-3-26 22:30
https://doi.org/10.1007/978-3-319-11656-3classification; feature selection; information extraction; kernel methods; learning algorithms; machine l作者: 錫箔紙 時間: 2025-3-27 03:15 作者: 考博 時間: 2025-3-27 05:20 作者: 定點 時間: 2025-3-27 11:55
https://doi.org/10.1007/978-3-030-00051-6In this paper we investigate reinforcement learning approaches for the popular computer game .. User-defined reward functions have been applied to .(0) learning based on .-greedy strategies in the standard Tetris scenario. The numerical experiments show that reinforcement learning can significantly outperform agents utilizing fixed policies.作者: MAPLE 時間: 2025-3-27 14:11 作者: CHOIR 時間: 2025-3-27 18:49
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162685.jpg作者: 晚來的提名 時間: 2025-3-28 01:51
Artificial Neural Networks in Pattern Recognition978-3-319-11656-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Aboveboard 時間: 2025-3-28 02:58
Large Margin Distribution Learninghe . is a fundamental issue of SVMs, whereas recently the margin theory for Boosting has been defended, establishing a connection between these two mainstream approaches. The recent theoretical results disclosed that the . rather than a single margin is really crucial for the generalization performa作者: 羞辱 時間: 2025-3-28 06:34 作者: 確定無疑 時間: 2025-3-28 11:44
Unsupervised Active Learning of CRF Model for Cross-Lingual Named Entity Recognitionformation extraction systems. Active learning has been proven to be effective in reducing manual annotation efforts for supervised learning tasks where a human judge is asked to annotate the most informative examples with respect to a given model. However, in most cases reliable human judges are not作者: 易碎 時間: 2025-3-28 17:15
Incremental Feature Selection by Block Addition and Block Deletion Using Least Squares SVRsthe discrete recognition rate. This leads to inferior feature selection results. To solve this problem, we propose using a least squares support vector regressor (LS SVR), instead of an LS support vector machine (LS SVM). We consider the labels (1/-1) as the targets of the LS SVR and the mean absolu作者: Perigee 時間: 2025-3-28 21:08 作者: cocoon 時間: 2025-3-29 01:04 作者: 集聚成團 時間: 2025-3-29 04:39
Hidden Markov Models Based on Generalized Dirichlet Mixtures for Proportional Data Modelingonal data modeling has been seldom mentioned in the literature. However, proportional data are a common way of representing large data in a compact fashion and often arise in pattern recognition applications frameworks. HMMs have been first developed for discrete and Gaussian data and their extensio作者: filicide 時間: 2025-3-29 10:43
Majority-Class Aware Support Vector Domain Oversampling for Imbalanced Classification Problemsiption to the minority class but in contrast to many other algorithms, awareness of samples of the majority class is used to improve the estimation process. The majority samples are incorporated in the optimization procedure and the resulting domain descriptions are generally superior to those witho作者: Amorous 時間: 2025-3-29 11:47 作者: LARK 時間: 2025-3-29 18:03
Dynamic Weighted Fusion of Adaptive Classifier Ensembles Based on Changing Data Streamsmble-based strategies have been proposed to preserve previously-acquired knowledge and reduce knowledge corruption, the fusion of multiple classifiers trained to represent different concepts can increase the uncertainty in prediction level, since only a sub-set of all classifier may be relevant. In 作者: 公理 時間: 2025-3-29 23:43
Combining Bipartite Graph Matching and Beam Search for Graph Edit Distance Approximation problem and can thus be solved in exponential time complexity only. A previously introduced approximation framework reduces the computation of GED to an instance of a linear sum assignment problem. Major benefit of this reduction is that an optimal assignment of nodes (including local structures) c作者: 幾何學家 時間: 2025-3-30 01:35 作者: 白楊魚 時間: 2025-3-30 07:08 作者: 歌唱隊 時間: 2025-3-30 11:31 作者: braggadocio 時間: 2025-3-30 14:36
Bio-Inspired Optic Flow from Event-Based Neuromorphic Sensor Inputis unlike biological mechanisms that are spike-based and independent of individual frames. The neuromorphic Dynamic Vision Sensor (DVS) [Lichtsteiner et al., 2008] provides a stream of independent visual events that indicate local illumination changes, resembling spiking neurons at a retinal level. 作者: 芳香一點 時間: 2025-3-30 20:22
Prediction of Insertion-Site Preferences of Transposons Using Support Vector Machines and Artificialn-site preferences is critically important in functional genomics and gene therapy studies. It has been found that the deformability property of the local DNA structure of the integration sites, called .., is of significant importance in the target-site selection process. We considered the .. profil作者: 自傳 時間: 2025-3-30 22:39 作者: 動物 時間: 2025-3-31 00:53 作者: Institution 時間: 2025-3-31 05:55
Large Margin Distribution Learningnce, and suggested to optimize the margin distribution by maximizing the margin mean and minimizing the margin variance simultaneously. Inspired by this recognition, we advocate the ., a promising research direction that has exhibited superiority in algorithm designs to traditional large margin learning.作者: Ergots 時間: 2025-3-31 09:38
0302-9743 on, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the lates作者: Emg827 時間: 2025-3-31 16:12 作者: Negligible 時間: 2025-3-31 21:16
Majority-Class Aware Support Vector Domain Oversampling for Imbalanced Classification Problemsocess. The majority samples are incorporated in the optimization procedure and the resulting domain descriptions are generally superior to those without knowledge about the majority class. Extensive experimental results support the validity of this approach.作者: 抵押貸款 時間: 2025-3-31 23:09
John Simpson,Vita Zidere,Owen I. Millery computer experiments, we show that performance of the proposed method is comparable with that with the criterion based on the weighted sum of the recognition error rate and the average margin error.作者: CURT 時間: 2025-4-1 02:50
Nadja Reissland,Barbara S. Kisilevskyd newly proposed Tangent Bundle Manifold Learning) motivated by various Data Analysis tasks. A new geometrically motivated algorithm that solves all the considered Dimensionality Reduction problems is presented.
