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Influence of nuclei segmentation on breast cancer malignancy classification

Lukasz Jelen, Thomas Fevens, Adam Krzyzak, Nico Karssemeijer, Maryellen L. Giger
<span title="2009-02-26">2009</span> <i title="SPIE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xfwg4fmybzazfktmdtzvhcujka" style="color: black;">Medical Imaging 2009: Computer-Aided Diagnosis</a> </i> &nbsp;
The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix.  ...  The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four  ...  obtained with Hough transform and textural segmentation but not as good as with level sets. • Fuzzy c-means does not require any initial boundary.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.811733">doi:10.1117/12.811733</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/micad/JelenFK09.html">dblp:conf/micad/JelenFK09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/etptbp4ucbctdbxsgrtmqxgoya">fatcat:etptbp4ucbctdbxsgrtmqxgoya</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170813083102/http://spectrum.library.concordia.ca/7709/1/Krzyzak_A_2009.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/8b/48/8b48e7460ef82c428207ad8d83b9adf6a9956d76.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.811733"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Brain Tumor Detection based on Machine Learning Algorithms

Komal Sharma, Akwinder Kaur, Shruti Gujral
<span title="2014-10-18">2014</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
The proposed work is divided into three parts: preprocessing steps are applied on brain MRI images, texture features are extracted using Gray Level Co-occurrence Matrix (GLCM) and then classification is  ...  Automated detection of tumor in Magnetic Resonance Imaging (MRI) is very crucial as it provides information about abnormal tissues which is necessary for planning treatment.  ...  It is known as feed forward because it does not contain any cycles and network output depends only on the current input instance. In MLP, each node is a neuron with a nonlinear activation function.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/18036-6883">doi:10.5120/18036-6883</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gcf76og54rdynjyzlur556whsy">fatcat:gcf76og54rdynjyzlur556whsy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602054047/https://research.ijcaonline.org/volume103/number1/pxc3896883.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c1/02/c1029db73a242801430602c108786cbe6796b7f2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/18036-6883"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Polyp Detection and Segmentation from Video Capsule Endoscopy: A Review

V. Prasath
<span title="2016-12-23">2016</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/au3ye363lzbdroopx7rzfyv63m" style="color: black;">Journal of Imaging</a> </i> &nbsp;
Though polyp detection in colonoscopy and other traditional endoscopy procedure based images is becoming a mature field, due to its unique imaging characteristics detecting polyps automatically in VCE  ...  is a hard problem.  ...  Acknowledgments: This work was initiated while the author was a post doctoral fellow at the Department  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jimaging3010001">doi:10.3390/jimaging3010001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ifkngz7v7rceteeihh3vhpw5uy">fatcat:ifkngz7v7rceteeihh3vhpw5uy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180728164615/https://res.mdpi.com/def50200bbe2a0e04b2f971ad64b63e87623630c3cb31074706242e5d29205aa77af478fcbebdab4cdabda8289c889b860f043d66ea5135fdbb3e378103c2877c6f668c8bda377aa03d02efe0d457a96ead2ba90f6bd448417d5e1a64781d7be6992dd17c158e94b1e7717db69df2e12a01435fa8b52c2a692217948160472125843c46736da00d0069485e6f347008bb71c61?filename=&amp;attachment=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9a/99/9a99af9495bab7f56278eff4f1ba04e63e8061f6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jimaging3010001"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Neural Network based Plant Identification using Leaf Characteristics Fusion

C. S.Sumathi, A. V. Senthil Kumar
<span title="2014-03-01">2014</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
Plant leaf images corresponding to six plant types are taken using a digital camera which are examined using three different modeling techniques, first based on Multi Layer Perceptron (MLP) Neural network  ...  Correlation based feature selection (CFS) is considered to produce a ranked list of attributes. Matlab is used to extract the leaf features such as edge and texture.  ...  Also this feature makes Gabor filters ideal for texture segmentation since simultaneous measurements in both spatial and spatial-frequency domains is required.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/15499-4141">doi:10.5120/15499-4141</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kkocce2h2rhare3tx2pkummlvm">fatcat:kkocce2h2rhare3tx2pkummlvm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602074313/https://research.ijcaonline.org/volume89/number5/pxc3894141.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e2/83/e2839674c79a455e4e3a29f1f3a8c08db33291e2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/15499-4141"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Generating segmented meshes from textured color images

Mario A.S. Lizier, David C. Martins, Alex J. Cuadros-Vargas, Roberto M. Cesar, Luis G. Nonato
<span title="">2009</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kekp3nlexfexzm4yg4msrqoove" style="color: black;">Journal of Visual Communication and Image Representation</a> </i> &nbsp;
An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion  ...  The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images.  ...  Therefore, the framework proposed in this work produces a segmented quality mesh representing structures contained in textured color images, a feature not found in other image based mesh generation techniques  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jvcir.2009.01.002">doi:10.1016/j.jvcir.2009.01.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7ms3x44y65fkvftr2xnbrsz37y">fatcat:7ms3x44y65fkvftr2xnbrsz37y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170921230815/http://www.lcad.icmc.usp.br/~nonato/pubs/malha_textura.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/56/d7/56d7a5ed94fefc91ac2458b15944ea728606e0bd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jvcir.2009.01.002"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Optimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data

Mustafa Ridha Mezaal, Biswajeet Pradhan, Maher Ibrahim Sameen, Helmi Zulhaidi Mohd Shafri, Zainuddin Md Yusoff
<span title="2017-07-16">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
These classifiers include parallel computation, which is superior to statistical classification approaches because it is non-parametric and does not require the prior knowledge of a distribution model  ...  Segmentation parameters and feature selection were respectively optimized using a supervised approach and correlation-based feature selection.  ...  Landslides should be differentiated from non-landslides based on the accurate segmentation of spatial and textural features.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app7070730">doi:10.3390/app7070730</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5mpzalusmfdhfisyxbkpivzpfq">fatcat:5mpzalusmfdhfisyxbkpivzpfq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719004629/https://opus.lib.uts.edu.au/bitstream/10453/123511/1/applsci-07-00730-v3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/67/92/67928b67fd408f27c9051fffc1fa3bb23703dda8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app7070730"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Patient oriented and robust automatic liver segmentation for pre-evaluation of liver transplantation

M. Alper Selver, Aykut Kocaoğlu, Güleser K. Demir, Hatice Doğan, Oğuz Dicle, Cüneyt Güzeliş
<span title="">2008</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wdwg5aetkjbgpga7kn2jevifmi" style="color: black;">Computers in Biology and Medicine</a> </i> &nbsp;
system and an MLP based complex one which are combined with a data-dependent and automated switching mechanism that decides to apply one of them.  ...  The efficiency in terms of the time requirement and the overall segmentation performance is achieved by introducing a novel modular classification system consisting of a K-Means based simple classification  ...  This strategy involves a segmentation method which does not utilize a common parameter set found from all patient data sets.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.compbiomed.2008.04.006">doi:10.1016/j.compbiomed.2008.04.006</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/18550045">pmid:18550045</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xj5plv74xrhqnlf5ojwimaewyi">fatcat:xj5plv74xrhqnlf5ojwimaewyi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20181008142047/http://kisi.deu.edu.tr:80/alper.selver/papers/cbm_liver.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7d/d8/7dd8b7e94c203107278b51af8b15590d5bd867b1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.compbiomed.2008.04.006"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Radiomics Detection of Pulmonary Hypertension via Texture-Based Assessments of Cardiac MRI: A Machine-Learning Model Comparison—Cardiac MRI Radiomics in Pulmonary Hypertension

Sarv Priya, Tanya Aggarwal, Caitlin Ward, Girish Bathla, Mathews Jacob, Alicia Gerke, Eric A. Hoffman, Prashant Nagpal
<span title="2021-04-28">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dwd4kjnpxfgfljif4cg2bgznpm" style="color: black;">Journal of Clinical Medicine</a> </i> &nbsp;
Cardiac MRI-based radiomics recognition of PH using texture features is feasible, even with preserved left ventricular ejection fractions.  ...  A multilayer perceptron model fitting using full feature sets was the best classifier model for both the primary analysis (AUC 0.862, accuracy 78%) and the subgroup analysis (AUC 0.918, accuracy 80%).  ...  While the MLP model does not perform embedded feature selection as each feature has an associated non-zero weight in the input layer, its ability to model non-linear relationships in all features is found  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jcm10091921">doi:10.3390/jcm10091921</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33925262">pmid:33925262</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u5gxk2q3gbe7hmgatanpotkcwi">fatcat:u5gxk2q3gbe7hmgatanpotkcwi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210502025618/https://res.mdpi.com/d_attachment/jcm/jcm-10-01921/article_deploy/jcm-10-01921-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fd/57/fd5764f7c54445b874eff13f190c9de4b4e0dfec.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jcm10091921"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Automatic Diagnosis of Breast Tissue [chapter]

Atef Boujelben, Hedi Tmar, Mohamed Abid, Jameleddine Mnif
<span title="2012-01-27">2012</span> <i title="InTech"> Advances in Cancer Management </i> &nbsp;
To attain our objective (CADi), we firstly show why and how to adapt Level Set-based approach in case of pseudo-detection, which is a semi-automatic detection by using level-set technique; and secondly  ...  Firstly, the identification of ROI is done using a level-set-based approach which includes edge and region criteria. Secondly, features are extracted, using shape/texture descriptors.  ...  This book presents newer advances in diagnosis and treatment of specific cancers, an evidence-based and realistic approach to the selection of cancer treatment, and cutting-edge laboratory developments  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/22565">doi:10.5772/22565</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lm5anq346zhq3copnh6ixarbka">fatcat:lm5anq346zhq3copnh6ixarbka</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180722030927/https://api.intechopen.com/chapter/pdf-download/26801" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a0/bf/a0bf4e8476c3b8984b218dd843affc6a3715a2ab.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5772/22565"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Automatic T1 bladder tumor detection by using wavelet analysis in cystoscopy images

Nuno R Freitas, Pedro M Vieira, Estevão Lima, Carlos S Lima
<span title="2018-02-02">2018</span> <i title="IOP Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zuggg3zvsfaatpw6invuoevl7a" style="color: black;">Physics in Medicine and Biology</a> </i> &nbsp;
Since a database with manual segmentations does not exist, only a qualitative evaluation was performed.  ...  Feature value is defined as a real number which encodes some information about a property of an object.  ...  Detection rates were obtained for the HSV, RGB, Lab, and ab configurations, and the features were extracted from the high-frequency sub-bands of the wavelet transform with the preprocessing.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1361-6560/aaa3af">doi:10.1088/1361-6560/aaa3af</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29271350">pmid:29271350</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ftxoslt5d5hblizf6vuuggbpue">fatcat:ftxoslt5d5hblizf6vuuggbpue</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210427133807/http://repositorium.sdum.uminho.pt/bitstream/1822/52816/4/Freitas_2018_Phys._Med._Biol._63_035031.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/de/4a/de4ad56221003712591e6e83cc6d796aeeb9e7cd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1361-6560/aaa3af"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> iop.org </button> </a>

An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images

Siew Chin Neoh, Worawut Srisukkham, Li Zhang, Stephen Todryk, Brigit Greystoke, Chee Peng Lim, Mohammed Alamgir Hossain, Nauman Aslam
<span title="2015-10-09">2015</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tnqhc2x2aneavcd3gx5h7mswhm" style="color: black;">Scientific Reports</a> </i> &nbsp;
Subsequently, a total of eighty features consisting of shape, texture, and colour information of the nucleus and cytoplasm subimages are extracted.  ...  Specifically, the proposed between-cluster evaluation is formulated based on the trade-off of several between-cluster measures of well-known feature extraction methods.  ...  As a result, FCS does not seem to perform well in the experiment when η j is fixed.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/srep14938">doi:10.1038/srep14938</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26450665">pmid:26450665</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4598743/">pmcid:PMC4598743</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/scr4uzpfhzg3zffbwm2nlqv34i">fatcat:scr4uzpfhzg3zffbwm2nlqv34i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190427224921/http://dro.deakin.edu.au/eserv/DU:30079902/lim-intelligentdecisionsupport-2015.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/08/c8/08c8f2e4b22c5e060646a41370aad8dec4b53727.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/srep14938"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598743" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformer [article]

Jinghua Zhang, Chen Li, Yimin Yin, Jiawei Zhang, Marcin Grzegorzek
<span title="2022-03-24">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
However, the automatic microorganism image analysis faces many challenges, such as the requirement of a robust algorithm caused by various application occasions, insignificant features and easy under-segmentation  ...  They play an essential role in environmental pollution control, disease prevention and treatment, and food and drug production.  ...  However, the setting of hidden layers in most works does not go through detailed theoretical or experimental analysis. In addition, some works do not provide the MLP implementation details.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2108.00358v3">arXiv:2108.00358v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/urt7siqpg5hrtdctxbfjhv4krq">fatcat:urt7siqpg5hrtdctxbfjhv4krq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220128024029/https://arxiv.org/pdf/2108.00358v2.pdf" title="fulltext PDF download [not primary version]" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/01/8a/018ab2bb9bbecda0199e73fdb5b649f84cb572b6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2108.00358v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Taking Fuzzy-Rough Application to Mars [chapter]

Changjing Shang, Dave Barnes, Qiang Shen
<span title="">2009</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The work allows the induction of low-dimensionality feature sets from sample descriptions of feature patterns of a much higher dimensionality.  ...  This paper presents a novel application of fuzzy-rough setbased feature selection (FRFS) for Mars terrain image classification.  ...  This paper presents an approach for performing large-scale Mars terrain image classification, by exploiting the recent advances in fuzzy-rough set-based feature selection techniques [6] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-10646-0_25">doi:10.1007/978-3-642-10646-0_25</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dclxkwnm6vfm7oym2nsr7i6kqi">fatcat:dclxkwnm6vfm7oym2nsr7i6kqi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170930230009/https://core.ac.uk/download/pdf/10184426.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0b/5a/0b5a16ed208b741b1c96b6baf6a1dabf1389755c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-10646-0_25"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

thermogram Breast Cancer Detection: A Comparative Study of Two Machine Learning Techniques

Fayez AlFayez, Mohamed W. Abo El-Soud, Tarek Gaber
<span title="2020-01-11">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
clustering, (3) feature extraction using signature boundary, and (4) classification in which two classifiers, Extreme Learning Machine (ELM) and Multilayer Perceptron (MLP), were used and compared.  ...  The results showed that ELM-based results were better than MLP-based ones with more than 19%.  ...  [1] suggested an automatic segmentation and then classification of normal and abnormal breast. The segmentation is based on an optimized Fast Fuzzy C-mean algorithm and Neutrosophic sets.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10020551">doi:10.3390/app10020551</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fkkbazk73nfllho7zpzyqe5szu">fatcat:fkkbazk73nfllho7zpzyqe5szu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200212150843/https://res.mdpi.com/d_attachment/applsci/applsci-10-00551/article_deploy/applsci-10-00551-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c5/c6/c5c6a596711ffb478766aba39d65be732b3baa59.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10020551"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Flower Classification Using Neural Network Based Image Processing

S.M. Mukane
<span title="">2013</span> <i title="IOSR Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/uuksgv35krdo3h6hiyizxfpbee" style="color: black;">IOSR Journal of Electronics and Communication Engineering</a> </i> &nbsp;
The proposed method is based on textural features such as Gray level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT). A flower image is segmented using a threshold based method.  ...  The data set has different flower images with similar appearance .The database of flower images is a mixture of images taken from World Wide Web and the images taken by us.  ...  In the training phase, from a given set of training images (segmented) the texture features (DWT and GLCM) is extracted.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/2834-0738085">doi:10.9790/2834-0738085</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/uhx5hnjc2jg6xlfci7yx32g3qu">fatcat:uhx5hnjc2jg6xlfci7yx32g3qu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180602045535/http://www.iosrjournals.org/iosr-jece/papers/Vol7-Issue3/N0738085.pdf?id=6678" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/31/79/31792f54f778483e5044d15c99b79dcc86b2850d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.9790/2834-0738085"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>
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