A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Information Filtering and Automatic Keyword Identification by Artificial Neural Networks
2000
European Conference on Information Systems
Preserved Fulltext
In this study we employ an artificial neural-network (ANN) as an alternative method for both filtering and term selection, and compare its effectiveness to "traditional" methods. ...
Information filtering (IF) systems usually filter data items by correlating a vector of terms (keywords) that represent the user profile with similar vectors of terms that represent the data items (e.g ...
Brief Introduction to Artificial Neural Networks Modeling ANN modeling is done by learning from known examples. A network of simple mathematical "neurons" is connected by weights. ...
dblp:conf/ecis/BogerKSS00
fatcat:tllwtk2brzdidipfez5m4vdto4
Chinese User Service Intention Classification Based on Hybrid Neural Network
2019
Journal of Physics, Conference Series
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Therefore, a hybrid neural network classification model based on BiLSTM and CNN is proposed to recognize users service intentions. ...
The model can fuse the temporal semantics and spatial semantics of the user descriptions. ...
This work was supported in part by the National Natural Science Foundation of China under Grant 71571136, in part by the National Basic Research Program of China under Grant 2014CB340404, and in part by ...
doi:10.1088/1742-6596/1229/1/012054
fatcat:ouwphoquzncivkyeitqxcheptu
Active Monitoring of Adverse Drug Reactions with Neural Network Technology
2017
Chinese Medical Journal
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Active Monitoring of Adverse Drug Reactions with Neural Network Technology ...
the era of artificial neural network research. ...
Experts need to check, track, and confirm the ADRs filtered by machine. After the artificial processing, a conclusion of ADRs can be drawn 4. ...
doi:10.4103/0366-6999.207468
pmid:28584215
pmcid:PMC5463482
fatcat:ojql5mlnavhi3i6cuktqhfmxdy
A Study of Various Speech Features and Classifiers used in Speaker Identification
2016
International Journal of Engineering Research and
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Keywords-Linear Predictive Cepstral Coefficients (LPCC), Mel Frequency Cepstral Coefficients (MFCC), Gaussian Mixture Model ( GMM), Vector Quantization (VQ), Hidden Markov Model ( HMM), Artificial Neural ...
Network (ANN) I. ...
Artificial Neural Networks An Artificial Neural Network is mathematical model that tries to simulate the structure and functions of biological neural networks. ...
doi:10.17577/ijertv5is020637
fatcat:eu4gvuqqsbalxlbqxhngo5itae
Ayurvedic Plant Identification using Image Processing and Artificial Intelligence
2021
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In this paper, a new technique to deployment problem is proposed based on the artificial bee colony (ABC) algorithm which is enhanced for the deployment of sensor networks to gain better performance by ...
Wireless networks provide small sensing, machine and wireless networking nodes. ...
Published : 10 Dec 2021 Keywords: ANN(Artificial Neural Network), KNN(k-nearest neighbors),
PNN(Probablistic Neural Network),SVM(Support Vector Machine ...
doi:10.32628/cseit217655
fatcat:ho3coezsdjchpi3222ikrugljm
Automatic Code Summarization: A Systematic Literature Review
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
By reading and analyzing relevant articles, we aim at obtaining a comprehensive understanding of the current status of automatic code summarization. ...
By fully elaborating current approaches in the field, our work sheds light on future research directions of program comprehension and comment generation. ...
The difference of timeframe is significant in the field of automatic code summarization, since the first application of artificial neural network to automatic code summarization was published by Iyer ...
arXiv:1909.04352v2
fatcat:xdxfdihcdfhbfnnilc2ofif4le
Segmentation of User Task Behavior by using Artificial Neural Network
2016
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Proposed work classifies the user query by combining query clustering boundary spread method with the neural network. ...
Proposed scheme reduces execution time as well because of using trained neural network. ...
assigning identification numbers to those keywords. ...
doi:10.5120/ijca2016912394
fatcat:5zmf24nyijfvdkjqg67bh2bg5y
Document Clustering using Learning from Examples
2012
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Information filtering (IF) systems usually filter data items by correlating a set of terms representing the user's interest with similar sets of terms representing the data items. ...
A new framework is described to classify large scale documents and retrieve the documents related to the user's query based on the application of trained artificial neural network (ANN) model. ...
Information filtering (IF) is a research area that provides tools for filtering out irrelevant information. ...
doi:10.5120/4872-7299
fatcat:gsnr5anizrfy5ggulf3ugsrw7q
Development of an intelligent searcher
2005
2005 International Conference on Industrial Electronics and Control Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
This article presents a description of the design and development of an Intelligent Searcher (a System based on an Intelligent Agent ). ...
In the second part, the implementation and general results are discussed. The analysis presented here covers the entire software development life cycle. ...
Neural Networks An artificial neuronal network (ANN) is an attempt for simulating through computational procedures the behavior of part of the human brain . ...
doi:10.1109/icieca.2005.1644381
fatcat:tuecpbvmdfevpkkfugrtbdxq7u
A review of Deep learning Techniques for COVID-19 identification on Chest CT images
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2022 pre-print arXiv:2208.00032v1 fatcat:lo74mk5m65bxvjemgsiist5rmi
Automatic identification of COVID-19 is a challenge for health care officials. ...
Relevant studies were collected by various databases such as Web of Science, Google Scholar, and PubMed. ...
In this study, papers are selected by the keywords Artificial Intelligence, COVID-19, Convolutional Neural Network, CT-images, and Deep Learning. ...
arXiv:2208.00032v2
fatcat:lfv5p633evholjztvroykrayba
An Improved Automatic Image Annotation Approach using Convolutional Neural Network-Slantlet Transform
2022
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
And they employed a deep learning convolutional neural network to build and improve image coding and annotation capabilities. ...
The automatic feature extraction for automatic annotation was the emphasis of this paper. ...
THE ARCHITECTURES OF THE CNN Convolutional neural networks (CNN) are artificial neural networks used to extract local features from data. ...
doi:10.1109/access.2022.3140861
fatcat:5ubshtj67fby7eawh2bbbwmjn4
Automatic Image Annotation via Combining Low-level Colour Feature with Features Learned from Convolutional Neural Networks
2018
NeuroQuantology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In addition to using low-level colour features from original images, we extract features learned from convolutional neural networks (CNNs). ...
Finally, when combining the two feature sets as inputs into the deep neural network-based AIA systems, we obtain the best performance in both cases. ...
This paper The artificial neural network in such aspects as structure principle and function features is closer to the human brain. ...
doi:10.14704/nq.2018.16.6.1612
fatcat:f3hspon52bbefndeacycpoim6i
SPI: Automated Identification of Security Patches via Commits
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2105.14565v1 fatcat:e7fwc3x7cndvpbc57qooizdztm
We devise a deep learning-based security patch identification system that consists of two neural networks: one commit-message neural network that utilizes pretrained word representations learned from our ...
commits dataset; and one code-revision neural network that takes code before and after revision and learns the distinction on the statement level. ...
Our work demonstrates that it is promising to apply deep neural networks to scale up patches identification via an automatic and evolutionary approach and improve the state of the art [77] in the industry ...
arXiv:2105.14565v2
fatcat:hlfmlekf5zcqtnsj5qugkza5du
A Study on Email Spam Filtering Techniques
2010
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Electronic mail is used daily by millions of people to communicate around the globe and is a mission-critical application for many businesses. ...
The necessity of effective spam filters increases. In this paper, we presented our study on various problems associated with spam and spam filtering methods, techniques. ...
Content based Spam Filtering Techniques -Neural Networks: The neural networks are quite famous to be well adapted for problems of classification. ...
doi:10.5120/1645-2213
fatcat:2szems4bhfaovlzodgjo6mqcw4
Applying the EFuNN Evolving Paradigm to the Recognition of Artefactual Beats in Continuous Seismocardiogram Recordings
[chapter]
2017
Communications in Computer and Information Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
The SCG data collection and the work of MDR, EV and PL were supported by the Italian Space Agency through the ASI 2013-061-I.0 and ASI 2013-079-R.0 grants. ...
Keywords: Seismocardiogram Á Evolving Fuzzy Neural Network Á Artfact identification
Introduction The assessment of both the electrical and mechanical activity of the heart are essential for the full ...
On this premise, we propose the use of the Evolving Fuzzy Neural Network (EFuNN) paradigm for the automatic artifact detection in the SCG signal. ...
doi:10.1007/978-3-319-65172-9_22
fatcat:rbk5shjicnfepgiagphcv3krua
« Previous
Showing results 1 — 15 out of 6,848 results