Adaptive multiclass support vector machine for multimodal data analysis

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[1]  Jing Zhang,et al.  Semantic Discriminative Metric Learning for Image Similarity Measurement , 2016, IEEE Transactions on Multimedia.

[2]  Bilal Alatas,et al.  Chaotic bee colony algorithms for global numerical optimization , 2010, Expert Syst. Appl..

[3]  Shiu Yin Yuen,et al.  Improving artificial bee colony with one-position inheritance mechanism , 2013, Memetic Comput..

[4]  Tianguang Chu,et al.  Learning in multimodal and mixmodal data: locality preserving discriminant analysis with kernel and sparse representation techniques , 2016, Multimedia Tools and Applications.

[5]  Qilian Liang,et al.  Situation Understanding Based on Heterogeneous Sensor Networks and Human-Inspired Favor Weak Fuzzy Logic System , 2009, IEEE Systems Journal.

[6]  Hugo Larochelle,et al.  A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Yiming Yan,et al.  Dynamic artificial bee colony algorithm for multi-parameters optimization of support vector machine-based soft-margin classifier , 2012, EURASIP J. Adv. Signal Process..

[8]  Hui Wang,et al.  An Adaptive Support Vector Machine-Based Workpiece Surface Classification System Using High-Definition Metrology , 2015, IEEE Transactions on Instrumentation and Measurement.

[9]  Guangwen Yang,et al.  An EnKF-based scheme to optimize hyper-parameters and features for SVM classifier , 2017, Pattern Recognit..

[10]  N. Sivakumaran,et al.  Grey wolf optimization based parameter selection for support vector machines , 2016 .

[11]  Aboul Ella Hassanien,et al.  A BA-based algorithm for parameter optimization of Support Vector Machine , 2017, Pattern Recognit. Lett..

[12]  Seok-Woo Jang,et al.  Texture feature-based text region segmentation in social multimedia data , 2015, Multimedia Tools and Applications.

[13]  Fenglian Li,et al.  An Enhanced Artificial Bee Colony-Based Support Vector Machine for Image-Based Fault Detection , 2015 .

[14]  Dong-Ling Xu,et al.  Circuit Tolerance Design Using Belief Rule Base , 2015 .

[15]  Chalavadi Krishna Mohan,et al.  Human action recognition using genetic algorithms and convolutional neural networks , 2016, Pattern Recognit..

[16]  Laura Diosan,et al.  Improving classification performance of Support Vector Machine by genetically optimising kernel shape and hyper-parameters , 2010, Applied Intelligence.

[17]  Bijaya K. Panigrahi,et al.  A Support Vector Machine-Firefly Algorithm based forecasting model to determine malaria transmission , 2014, Neurocomputing.

[18]  Xiuzhen Cheng,et al.  KUPS: Knowledge-based ubiquitous and persistent sensor networks for threat assessment , 2008 .

[19]  Christian Wolf,et al.  ModDrop: Adaptive Multi-Modal Gesture Recognition , 2014, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Long Xu,et al.  Multimodal deep learning for solar radio burst classification , 2017, Pattern Recognit..

[21]  Qilian Liang,et al.  KUPS: Knowledge-based Ubiquitous and Persistent Sensor networks for Threat Assessment , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.

[22]  Ivan Zelinka,et al.  A survey on evolutionary algorithms dynamics and its complexity - Mutual relations, past, present and future , 2015, Swarm Evol. Comput..

[23]  Petros Daras,et al.  A unified framework for multimodal retrieval , 2013, Pattern Recognit..

[24]  George K. Matsopoulos,et al.  Multimodal genetic algorithms-based algorithm for automatic point correspondence , 2010, Pattern Recognit..

[25]  Gang Wang,et al.  Towards an optimal support vector machine classifier using a parallel particle swarm optimization strategy , 2014, Appl. Math. Comput..

[26]  Alexandros Iosifidis,et al.  Multi-class Support Vector Machine classifiers using intrinsic and penalty graphs , 2016, Pattern Recognit..

[27]  Palaiahnakote Shivakumara,et al.  A new multi-modal approach to bib number/text detection and recognition in Marathon images , 2017, Pattern Recognit..

[28]  Dervis Karaboga,et al.  Dynamic clustering with improved binary artificial bee colony algorithm , 2015, Appl. Soft Comput..

[29]  Gabriela Oliveira Biondi,et al.  Setting Parameters for Support Vector Machines using Transfer Learning , 2015, Journal of Intelligent & Robotic Systems.

[30]  Marc Moonen,et al.  Joint DOA and multi-pitch estimation based on subspace techniques , 2012, EURASIP J. Adv. Signal Process..

[31]  Li Chen,et al.  Hierarchical multi-feature fusion for multimodal data analysis , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[32]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[33]  Xudong Jiang,et al.  Multi-modal and multi-layout discriminative learning for placental maturity staging , 2017, Pattern Recognit..

[34]  Xiuzhen Cheng,et al.  NEW: Network-Enabled Electronic Warfare for Target Recognition , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[35]  Zheng Cao,et al.  Robust support vector machines based on the rescaled hinge loss function , 2017, Pattern Recognition.

[36]  Yuan-Hai Shao,et al.  MLTSVM: A novel twin support vector machine to multi-label learning , 2016, Pattern Recognit..

[37]  Mansour Jamzad,et al.  Efficient multi-modal fusion on supergraph for scalable image annotation , 2015, Pattern Recognit..

[38]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[39]  Xiuzhen Cheng,et al.  Opportunistic Sensing in Wireless Sensor Networks: Theory and Application , 2014, IEEE Trans. Computers.

[40]  Jim Jing-Yan Wang,et al.  Joint learning of cross-modal classifier and factor analysis for multimedia data classification , 2015, Neural Computing and Applications.

[41]  Jianping Fan,et al.  Hierarchical learning of multi-task sparse metrics for large-scale image classification , 2017, Pattern Recognit..

[42]  Javad Hamidzadeh,et al.  New Hermite orthogonal polynomial kernel and combined kernels in Support Vector Machine classifier , 2016, Pattern Recognit..

[43]  Xin Zhang,et al.  A micro-artificial bee colony based multicast routing in vehicular ad hoc networks , 2017, Ad Hoc Networks.

[44]  Shahryar Rahnamayan,et al.  Micro-differential evolution with vectorized random mutation factor , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[45]  Liyuan Zhang,et al.  Efficient relation extraction method based on spatial feature using ELM , 2014, Neural Computing and Applications.

[46]  Weizhi Nie,et al.  Cross-domain semantic transfer from large-scale social media , 2014, Multimedia Systems.

[47]  Yang Liu,et al.  Structure-Constrained Low-Rank and Partial Sparse Representation with Sample Selection for image classification , 2016, Pattern Recognit..

[48]  Yu Xue,et al.  Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification , 2017, Pattern Recognit..