A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Empirical Mode Decomposition Pre-Process for Higher Accuracy Hyperspectral Image Classification
2008
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium
Preserved Fulltext
This paper proposes Empirical Mode Decomposition (EMD) based pre-process to increase classification accuracy of hyperspectral images. ...
Support vector machine (SVM) is used to show the classification performance of the proposed approach. ...
For this reason, classification tools are needed to summarize information. Support vector machine (SVM) based approaches have recently been proposed to classify hyperspectral images. ...
doi:10.1109/igarss.2008.4779150
dblp:conf/igarss/DemirE08b
fatcat:3iiqwjqngncb5a4pjxsqpu4sju
MetaSel: a metaphase selection tool using a Gaussian-based classification technique
2013
BMC Bioinformatics
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
Several image parameters were examined and used for creating rule-based classification. The threshold value for each parameter is determined using a statistical model. ...
The selection of suitable metaphase chromosome spreads thus represents a major bottleneck for conventional cytogenetic analysis. ...
Acknowledgements The authors would like to thank the research team from the Center for Medical ...
doi:10.1186/1471-2105-14-s16-s13
pmid:24564477
pmcid:PMC4015449
fatcat:os5yzrnsandmrjbn3ss7bcsitq
A comparative study of image processing thresholding algorithms on residual oxide scale detection in stainless steel production lines
2019
Procedia Manufacturing
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.
The present work is intended for residual oxide scale detection and classification through the application of image processing techniques. ...
From a previous detailed study over reflectance of residual oxide defect, we present a comparative study of algorithms for image segmentation based on thresholding methods. ...
., management for supporting this investigation and the Information Systems and Quality Control departments for its help and essential suggestions offered in this research. ...
doi:10.1016/j.promfg.2019.07.049
fatcat:vcvcwkecnrddzlksqsjklydsai
Classification of Mammograms Using Bidimensional Empirical Mode Decomposition Based Features and Artificial Neural Network
2013
International Journal of Bio-Science and Bio-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 2018; you can also visit the original URL.
The file type is application/pdf.
., Bidimensional Empirical Mode Decomposition (BEMD) for mammogram images. The EMD is fully adaptive and data driven technique. ...
Three experiments, i) classification of normal mammogram and calcification, ii) classification of mass tissue and calcification and iii) classification of normal, mass and calcification have been performed ...
Performance analysis of all the classifications is shown in Table IV . ...
doi:10.14257/ijbsbt.2013.5.6.18
fatcat:353ptrjabbgnfbd44qe4u7bhda
SAR Target Detection Method Based on Empirical Mode Decomposition
2012
Advanced Engineering Forum
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.
So this paper proposes the new synthetic aperture radar (SAR) image target detection algorithm after analyzing the characteristics of EMD and SAR images. ...
Empirical mode decomposition (EMD) is a new signal processing theory, and it is very much fitting for non-stationary signal processing, such as radar signal. ...
If it is decomposed with EMD, more accurate target information can be obtained, which is very much fitting for target detection, classification and recognition. ...
doi:10.4028/www.scientific.net/aef.6-7.496
fatcat:mtir4f2wunbo3et4fzlz7aiety
An Improved Quantitative Analysis Method for Plant Cortical Microtubules
2014
The Scientific World 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.
In summary, the results indicate that this method is feasible and effective for the image quantitative analysis of plant cortical microtubules. ...
In this paper, Bidimensional Empirical Mode Decomposition (BEMD) algorithm was applied in the image preprocessing of the original microtubule image. ...
Acknowledgment The authors would like to acknowledge professor Ming Yuan from China Agricultural University for gifting the GFP-TUA6 Arabidopsis seed. ...
doi:10.1155/2014/637183
pmid:24744684
pmcid:PMC3972865
fatcat:rizzprhk6fey3btb4tbuoy4l74
IMAGE EMPIRICAL MODE DECOMPOSITION: A NEW TOOL FOR IMAGE PROCESSING
2009
Advances in Adaptive Data Analysis
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 this study we give an overview of the state-of-the-art methods to decompose an image into a number of IMFs and a residue image with a minimum number of extrema points, together with the use of the method ...
Image empirical mode decomposition (IEMD) is an empirical mode decomposition concept used in Hilbert-Huang transform (HHT) expanded into two dimensions for the use on images. ...
Texture analysis To perform good texture analysis we need a feature vector describing the texture information in the image. ...
doi:10.1142/s1793536909000138
fatcat:k73h7i66jjeu3miirq42rnwltu
Medical Image Retrieval Using Empirical Mode Decomposition with Deep Convolutional Neural Network
2020
BioMed Research International
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.
We achieve a total IRMA error of 43.21 and a mean average precision of 0.86 for retrieval task and IRMA error of 68.48 and F1 measure of 0.66 on classification task, which is the best result compared with ...
Content-based medical image retrieval (CBMIR) systems attempt to search medical image database to narrow the semantic gap in medical image analysis. ...
Acknowledgments The authors would like to thank Bo Wen ...
doi:10.1155/2020/6687733
pmid:33426062
pmcid:PMC7781707
fatcat:rgn4jwke2vdsthadbla35pl754
Recurrent Residual Learning for Sequence Classification
2016
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
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.
In this paper, we explore the possibility of leveraging Residual Networks (ResNet), a powerful structure in constructing extremely deep neural network for image understanding, to improve recurrent neural ...
In addition, we propose two novel models which combine the best of both residual learning and LSTM. Experiments show that the new models significantly outperform LSTM. ...
Gated Residual RNN Identity connections in ResNet are important for propagating the single input image information to higher layers of CNN. ...
doi:10.18653/v1/d16-1093
dblp:conf/emnlp/WangT16
fatcat:hgsvtfx3xvb6lkthhz2abgfsim
Real-Time Classification of Transient Events in Synoptic Sky Surveys
2011
Proceedings of the International Astronomical Union
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.
Other Versions
An automated, rapid classification of transient events detected in the modern synoptic sky surveys is essential for their scientific utility and effective follow-up using scarce resources. ...
We are exploring a variety of novel automated classification techniques, mostly Bayesian, to respond to these challenges, using the ongoing CRTS sky survey as a testbed. ...
If the images are properly matched, a transient stands out as a positive residual, though when used with white light (as is the case with CRTS) the difference images tend to have bipolar residuals, thus ...
doi:10.1017/s1743921312001056
fatcat:r6o54bykabemtbj3wgfwo5usle
Pulsar Candidate Recognition Using Deep Neural Network Model
2022
Electronics
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, we solved this problem from the perspective of intelligent image processing and a deep neural network model AR_Net was proposed in this paper. ...
model to learn pivotal information was improved. ...
Acknowledgments: The research work described in this paper was supported by the Joint Research Fund in Astronomy (U2031136) under cooperative agreement between the NSFC and CAS and ...
doi:10.3390/electronics11142216
fatcat:tnvca7grrzdddhyt5thuo4xnja
Image Fusion in Hyperspectral Image Classification using Genetic Algorithm
2016
Indonesian Journal of Electrical Engineering and Computer 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 2017; you can also visit the original URL.
The file type is application/pdf.
<p>Hyperspectral remote sensors collect image data for a large number of narrow, adjacent spectral bands. ...
This method increases classification accuracy of hyperspectral image.</p> ...
This method increases the classification accuracy both in qualitative and quantitative analysis. ...
doi:10.11591/ijeecs.v2.i3.pp703-711
fatcat:t4jj3nlesjehhggl7lx6qomu5i
COMPARISOM OF WAVELET-BASED AND HHT-BASED FEATURE EXTRACTION METHODS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
2012
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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 2017; you can also visit the original URL.
The file type is application/pdf.
In this study, the time-frequency analysis methods are used to extract the features for hyperspectral image classification. ...
Therefore, we can get a small number of salient features, reduce the dimensionality of hyperspectral images and keep the accuracy of classification results. ...
The residual information is also considered in this spectrum. After that, the M largest values in the Hilbert spectrum are selected as the important features of the spectral curve for classification. ...
doi:10.5194/isprsarchives-xxxix-b7-121-2012
fatcat:idhgjawf5vebhdr7by3zvyz3ga
Spatial frequency based video stream analysis for object classification and recognition in clouds
2016
Proceedings of the 3rd IEEE/ACM International Conference on Big Data Computing, Applications and Technologies - BDCAT '16
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 video data is then processed for object classification to extract useful information. ...
We present a cloud-based blur and illumination invariant approach for object classification from images and video data. ...
[17] in which the phase information was calculated within a local window for every image position. ...
doi:10.1145/3006299.3006322
dblp:conf/bdc/YaseenAA16
fatcat:kfxjsixrc5ekbji6rbeynxfya4
Motion vector processing using the color information
2009
2009 16th IEEE International Conference on Image Processing (ICIP)
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 2010; you can also visit the original URL.
The file type is application/pdf.
By making use of the color information for the received residual energy calculation, these unreliable motion vectors can effectively be identified. ...
In this paper, we investigate color distribution around object edges and further exploit this information for motion vector reliability analysis. ...
For selecting the α value, we only need to be careful not to overemphasize the color since the luminance is still the fundamental elements of the image. ...
doi:10.1109/icip.2009.5413657
dblp:conf/icip/HuangN09a
fatcat:jdtn7nfdafgznbx7nu5ckhif5e
« Previous
Showing results 1 — 15 out of 73,667 results