The 2013 International Joint Conference on Neural Networks (IJCNN)最新文献_第9页

Multi-circle detection for bladder cancer diagnosis based on artificial immune systems 基于人工免疫系统的膀胱癌多环检测诊断

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6707120

D. Lu, Xiao-Hua Yu

引用次数: 1

The use of optical and sonar images in the human and dolphin brain for image classification 利用人类和海豚大脑中的光学和声纳图像进行图像分类

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6706892

Sepehr Jalali, P. Seekings, Cheston Tan, Aiswarya Ratheesh, Joo-Hwee Lim, Elizabeth A. Taylor

引用次数: 0

Robust image representation and decomposition by Laplacian regularized latent low-rank representation 基于拉普拉斯正则化潜在低秩表示的鲁棒图像表示与分解

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6707051

Zhao Zhang, Shuicheng Yan, Mingbo Zhao

{"title":"Robust image representation and decomposition by Laplacian regularized latent low-rank representation","authors":"Zhao Zhang, Shuicheng Yan, Mingbo Zhao","doi":"10.1109/IJCNN.2013.6707051","DOIUrl":"https://doi.org/10.1109/IJCNN.2013.6707051","url":null,"abstract":"This paper discusses the image representation and decomposition problem using enhanced low-rank representation. Technically, we propose a Regularized Low-Rank Representation framework referred to as rLRR that is motivated by the fact that Latent Low-Rank Representation (LatLRR) delivers robust and promising results for image representation and feature extraction through recovering the hidden effects, but the locality among both similar principal and salient features to be encoded are not preserved in the original LatLRR formulation. To address this problem for obtaining enhanced performance, rLRR is proposed through incorporating an appropriate Laplacian regularization term that allows us to keep the local geometry of close features. Similar to LatLRR, rLRR decomposes a given data matrix from two directions by calculating a pair of low-rank matrices. But the similarities among principal features and salient features can be clearly preserved by rLRR. Thus the correlated features can be well grouped and the robustness of representations can also be effectively improved. The effectiveness of rLRR is examined by representation and recognition of real images. Results verified the validity of our presented rLRR technique.","PeriodicalId":376975,"journal":{"name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122175023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Novelty estimation in developmental networks: Acetylcholine and norepinephrine 发育网络中的新颖性估计:乙酰胆碱和去甲肾上腺素

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6706722

Jordan A. Fish, Lisa Ossian, J. Weng

引用次数: 1

Bubbles in the robot 机器人里的气泡

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6706718

T. Trappenberg

引用次数: 0

A novel cost sensitive neural network ensemble for multiclass imbalance data learning 一种用于多类不平衡数据学习的代价敏感神经网络集成

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6706980

Peng Cao, Bo Li, Dazhe Zhao, Osmar R Zaiane

{"title":"A novel cost sensitive neural network ensemble for multiclass imbalance data learning","authors":"Peng Cao, Bo Li, Dazhe Zhao, Osmar R Zaiane","doi":"10.1109/IJCNN.2013.6706980","DOIUrl":"https://doi.org/10.1109/IJCNN.2013.6706980","url":null,"abstract":"Traditional classification algorithms can be limited in their performance on imbalanced datasets. In recent years, the imbalanced data learning problem has drawn significant interest. In this work, we focus on designing modifications to neural network, in order to appropriately tackle the problem of multiclass imbalance. We propose a method that combines two ideas: diverse random subspace ensemble learning with evolutionary search, to improve the performance of neural network on multiclass imbalanced data. An evolutionary search technique is utilized to optimize the misclassification cost under the guidance of imbalanced data measures. Moreover, the diverse random subspace ensemble employs the minimum overlapping mechanism to provide diversity so as to improve the performance of the learning and optimization of neural network. Furthermore, the ensemble framework can determine the optimal amount of non-redundant components automatically. We have demonstrated experimentally using UCI datasets that our approach can achieve significantly better result than state-of-the-art methods for imbalanced data.","PeriodicalId":376975,"journal":{"name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126691897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Unsupervised multimodal feature learning for semantic image segmentation 语义图像分割的无监督多模态特征学习

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6706748

Deli Pei, Huaping Liu, Yulong Liu, F. Sun

引用次数: 18

Adaptive linear learning for on-line harmonic identification: An overview with study cases 在线谐波辨识的自适应线性学习:附研究案例综述

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6706970

P. Wira, Thien-Minh Nguyen

引用次数: 4

Neural inverse optimal control for a linear induction motor 线性感应电动机的神经逆最优控制

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6707092

V. Lopez, E. Sánchez, A. Alanis

引用次数: 2

Memristor SPICE model and crossbar simulation based on devices with nanosecond switching time 基于纳秒开关时间器件的忆阻器SPICE模型及交叉棒仿真

The 2013 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2013-08-01 DOI: 10.1109/IJCNN.2013.6706773

C. Yakopcic, T. Taha, G. Subramanyam, R. Pino

引用次数: 96