Filters








70,736 Hits in 5.9 sec

Fully complex-valued ELM classifiers for human action recognition

R. Venkatesh Babu, S. Suresh
2011 The 2011 International Joint Conference on Neural Networks  
In this paper, we present a fast learning neural network classifier for human action recognition. The proposed classifier is a fully complex-valued neural network with a single hidden layer.  ...  The fast leaning fully complex-valued neural classifier is used for recognizing human actions accurately.  ...  DESCRIPTION OF THE CLASSIFIER In this section, we present the detailed description of fast learning fully complex-valued neural classifier. A.  ... 
doi:10.1109/ijcnn.2011.6033588 dblp:conf/ijcnn/BabuS11 fatcat:xdb55uadvzajjhv6v5ov2jdrya

Design of Near-Optimal Classifier Using Multi-Layer Perceptron Neural Networks for Intelligent Sensors

Nadir N. Charniya
2013 International Journal of Modeling and Optimization  
The Multi-layer Perceptron Neural Networks (MLP NN) are well known for their simplicity, ease of training for small-scale problems, and suitability for online implementation.  ...  Index Terms-Classifier, neural networks, multi-layer percptron, intelligent sensors.  ...  NEURAL NETWORKS AS CLASSIFIER The central problem in classification is to define the shape Design of Near-Optimal Classifier Using Multi-Layer Perceptron Neural Networks for Intelligent Sensors Nadir N  ... 
doi:10.7763/ijmo.2013.v3.234 fatcat:4isht45qwza6lhxlt5elvfrkcm

A Framework For Intelligent Multi Agent System Based Neural Network Classification Model [article]

Roya Asadi, Norwati Mustapha, Nasir Sulaiman
2009 arXiv   pre-print
In this paper, we proposed a framework of intelligent agent based neural network classification model to solve the problem of gap between two applicable flows of intelligent multi agent technology and  ...  We consider the new Supervised Multilayers Feed Forward Neural Network (SMFFNN) model as an intelligent classification for learning model in the framework.  ...  Each torque shows a real worth of each value between whole values in matrix.  ... 
arXiv:0910.2029v1 fatcat:x5xzko3fqfbhtjcuur7vnmyw7u

The Impact of Randomization on Circular-Complex Extreme Learning Machine for Real Valued Classification Problems

Ram GovindSingh, Akhil Pandey
2014 International Journal of Computer Applications  
Performance of proposed classifier ensemble is evaluated using a set of benchmark real-valued classification problems from the University of California, Irvine machine learning repository.  ...  Extreme Learning Machine (ELM) has recently emerged as a fast classifier giving good performance.  ...  R.Savitha et. al [7] proposed a Fast learning circular complex valued extreme learning machine (CC-ELM) for the classification of real valued data sets in complex domain.CC-ELM uses sin(z) as circular  ... 
doi:10.5120/18043-8922 fatcat:nxh5l5ofp5c4hokseptupwtm3u

Application and Verification of Algorithm Learning Based Neural Network [article]

Rizwana Kalsoom, Moomal Qureshi
2015 arXiv   pre-print
Algorithm learning based neural network integrating feature selection and classification.  ...  This paper has been withdrawn by the author due to a crucial accuracy error in Fig. 5. For precise performance of ALBNN please refer to Yoon et al.'s work in the following article. Yoon, H., Park, C.  ...  Artificial Neural Networks (ANNs) have emerges as an effective tool and been applied to various real life problems.  ... 
arXiv:1406.2614v4 fatcat:croulvr4s5gbbmxhsgk626awei

Generalized neural trees for pattern classification

G.L. Foresti, C. Micheloni
2002 IEEE Transactions on Neural Networks  
In particular, the GNT model displays good classification performances for training sets having complex distributions.  ...  In this paper, a new neural tree (NT) model, the generalized NT (GNT), is presented.  ...  This problem is deemed a difficult task because of the complexity of learning the boundary regions of the TS.  ... 
doi:10.1109/tnn.2002.804290 pmid:18244549 fatcat:jlzlm5tnt5gwfpwgd3v54q6qiy

Randomness in Circular - Complex Extreme Learning Machine Vs Voting Based Extreme Learning Machine with Accuracy Based Ensemble Pruning: A Review

Ashish Gupta
2019 IARJSET  
Extreme Learning Machine is a fast single layer feed forward neural network for real valued classification. It suffers from the problem of instability and over fitting.  ...  Performance of proposed classifier ensemble is evaluated using a set of benchmark real-valued classification problems from the University of California, Irvine machine learning repository.  ...  R.Savitha et. al [6] proposed a Fast learning circular complex valued extreme learning machine (CC-ELM) for the classification of real valued data sets in complex domain.CC-ELM uses sin(z) as circular  ... 
doi:10.17148/iarjset.2019.6510 fatcat:2d6pg4jhgve3ljxcutltitcway

Quaternion softmax classifier

Rui Zeng, Lotfi Senhadji, Huazhong Shu, Zhuhong Shao, Jiasong Wu
2014 Electronics Letters  
in complex (or real) domain.  ...  Therefore, quaternion features classifiers with high classification accuracy and fast convergence rate are highly needed.  ...  Most classification problem used 3-layers neural network. In learning phase of QBPNN and proposed method, we used min-Func matlab toolbox [10] for numerical optimization.  ... 
doi:10.1049/el.2014.2526 fatcat:hicgq4mrbbbrndjxb7afbborha

An Efficient PSO Based Ensemble Classification Model on High Dimensional Datasets

Lalitha Kumari G, Naga Malleswara Rao N
2017 International Journal of Soft Computing  
Ensemble classifier is one of the scalable models for extreme learning machine due to its high efficiency, the fast processing speed for real-time applications.  ...  As the size of the biomedical databases are growing day by day, finding an essential features in the disease prediction have become more complex due to high dimensionality and sparsity problems.  ...  Ensemble classifier is one of the scalable models for extreme learning machine due to its high efficiency, the fast processing speed for real-time applications.  ... 
doi:10.5121/ijsc.2017.8401 fatcat:kszowdxuu5emrg2pzd2cfcihrq

A Frequency Pattern Mining Model Based on Deep Neural Network for Real-Time Classification of Heart Conditions

Hyun Yoo, Soyoung Han, Kyungyong Chung
2020 Healthcare  
The objective of this paper is to provide the model for the personalized heart condition classification in combination with the fast and effective preprocessing technique and deep neural network in order  ...  A personalized analysis technique is a basis for judging the risk factors of personal cardiovascular disorders in real-time.  ...  In a multi-layer neural network, the depth of hidden layers become deep depending on problem complexity [22] .  ... 
doi:10.3390/healthcare8030234 pmid:32722657 pmcid:PMC7551638 fatcat:7xt3re2f7vgblcmjeku5b4kbmq

Survey Paper on Classifiers for Machine Learning

Dr. Manjunath M, Prof. Venkatesha G, Dr. Dinesh S
2019 Zenodo  
Complexity is your problem, classifiers may offer a solution.  ...  The classifiers concept has inspired a multitude of implementations adapted to manage the different problem domains to which it has been applied (e.g., autonomous robotics, classification, knowledge discovery  ...  Naive Bayes classifier Naive Bayes is a simple technique for constructing classifiers: models that assign class labels to problem instances, represented as vectors of feature values, where the  ... 
doi:10.5281/zenodo.3407940 fatcat:jrmbjjxn3nhbtes2pq6bk5hw3i

Feature selection from colon cancer dataset for cancer classification using Artificial Neural Network

Md. Akizur Rahman, Ravie Chandren Muniyandi
2018 International Journal on Advanced Science, Engineering and Information Technology  
Feature selection has become a vital task to apply data mining algorithms effectively in the real-world problems for classification.  ...  This study proposed Artificial Neural Network (ANN) for cancer classification by the feature selection on colon cancer dataset.  ...  It is consequently beneficial for real-world classification problem to receive a superior connection as a fundamental idea [5] - [7] .  ... 
doi:10.18517/ijaseit.8.4-2.6790 fatcat:7wljzlr2nncmrfdnnn2iz4kfla

Artificial Neural Network based Intrusion Detection System: A Survey

Bhavin Shah, Bhushan H Trivedi
2012 International Journal of Computer Applications  
In simple approach we will discuss on how Back Propagation Neural Network (BPNN), Self Organizing Maps (SOM), Support Vector Machine (SVM), and Simulated Annealing Neural Network (SA) are used for anomaly  ...  Number of the researchers has already shown the importance of the various Artificial Neural Network (ANN) based techniques for anomaly detection.  ...  One major problem with SOM is getting the right data. Unfortunately one needs a value for each dimension of each member of samples in order to generate a map.  ... 
doi:10.5120/4823-7074 fatcat:vaozrxrnrrgxbaox2ucxwlkwuq

Robust Underwater Fish Detection Using an Enhanced Convolutional Neural Network

Dipta Gomes, American International University-Bangladesh (AIUB), Dhaka, Bangladesh, A.F.M. Saifuddin Saif
2021 International Journal of Image Graphics and Signal Processing  
All this is carried out by overcoming difficulties underwater through a novel technique that can be integrated into an Underwater Autonomous Vehicle and can be classified as robust in nature.  ...  As a result, techniques that are already well established will be used for overall enhancement of those images.  ...  A Conventional Neural Network is used for classification, where the input images are used as sonar images. The fast object detection makes the system more real time.  ... 
doi:10.5815/ijigsp.2021.03.04 fatcat:sa6bbpulufevfazhl2hqzvwu5q

Neural Network Modelling for Sports Performance Classification as a Complex Socio-Technical System

Ivars Namatēvs, Ludmila Aleksejeva, Inese Poļaka
2016 Information Technology and Management Science  
The aim of this article is to create a theoretical framework and structurally connect the sports and multi-layer artificial neural network domains through: (a) describing sports as a complex socio-technical  ...  system; (b) identification of pre-processing subsystem for classification; (c) feature selection by using data-driven valued tolerance ratio method; (d) design predictive system model of sports performance  ...  Today the fast-changing environment presents a challenge for complexity research practitioners, who rely on the systems theory [10] .  ... 
doi:10.1515/itms-2016-0010 fatcat:jad37h7xcner7hrhfekcwzldwy
« Previous Showing results 1 — 15 out of 70,736 results