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Weather Classification: A new multi-class dataset, data augmentation approach and comprehensive evaluations of Convolutional Neural Networks

Jose Carlos Villarreal Guerra, Zeba Khanam, Shoaib Ehsan, Rustam Stolkin, Klaus McDonald-Maier
<span title="">2018</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/74wwkahd4bbfnlle2od7myqj4u" style="color: black;">2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)</a> </i> &nbsp;
In this paper, we have created a new open source dataset consisting of images depicting three classes of weather i.e rain, snow and fog called RFS Dataset.  ...  A novel algorithm has also been proposed which has used super pixel delimiting masks as a form of data augmentation, leading to reasonable results with respect to ten Convolutional Neural Network architectures  ...  The first one is exploring the use of superpixel masks as a data augmentation technique, considering different Convolutional Neural Network (CNN) architectures for the feature extraction process when classifying  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ahs.2018.8541482">doi:10.1109/ahs.2018.8541482</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ahs/GuerraKESM18.html">dblp:conf/ahs/GuerraKESM18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fzqq7x7npvefhehnvvykfddkha">fatcat:fzqq7x7npvefhehnvvykfddkha</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190430015342/http://repository.essex.ac.uk/23547/1/1808.00588v1.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/77/54/7754e9c44284131773dd6c6c2cc90feb055879a1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ahs.2018.8541482"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A CNN-RNN Architecture for Multi-Label Weather Recognition [article]

Bin Zhao, Xuelong Li, Xiaoqiang Lu, Zhigang Wang
<span title="2019-04-24">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Specifically, a CNN-RNN based multi-label classification approach is proposed in this paper.  ...  The new constructed datasets will be available at https://github.com/wzgwzg/Multi-Label-Weather-Recognition.  ...  The Multi-Label Weather Classification Dataset To further evaluate the proposed approach, we construct a new dataset from scratch, which contains 10000 images from 5 weather classes, i.e., 'sunny', 'cloudy  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.10709v1">arXiv:1904.10709v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pixyszc4cnehldcwrv7lkzcsue">fatcat:pixyszc4cnehldcwrv7lkzcsue</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200930183438/https://arxiv.org/pdf/1904.10709v1.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/83/4c/834c1a057a90cacad3e36b35387bd4ea9fa80727.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.10709v1" 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>

Multi-Scale Convolutional Neural Networks for Time Series Classification [article]

Zhicheng Cui and Wenlin Chen and Yixin Chen
<span title="2016-05-11">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To address these problems, we propose a novel end-to-end neural network model, Multi-Scale Convolutional Neural Networks (MCNN), which incorporates feature extraction and classification in a single framework  ...  We conduct comprehensive empirical evaluation with various existing methods on a large number of benchmark datasets, and show that MCNN advances the state-of-the-art by achieving superior accuracy performance  ...  ACKNOWLEDGMENTS The authors are supported in part by the IIS-1343896, DBI-1356669, and III-1526012 grants from the National Science Foundation of the United States, a Microsoft Research New Faculty Fellowship  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1603.06995v4">arXiv:1603.06995v4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bhxrj22ijzbahikm3fkjknwrvu">fatcat:bhxrj22ijzbahikm3fkjknwrvu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191019022324/https://arxiv.org/pdf/1603.06995v4.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/9e/8c/9e8cce4d2d0bc575c6a24e65398b43bf56ac150a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1603.06995v4" 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>

MATERIAL CLASSIFICATION SYSTEM: LITERATURE SURVEY

Shama Holla, Shivani Bonageri, Shravya Shetty, K Panimozhi
<span title="2020-06-30">2020</span> <i title="IJEAST"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/namhphsg6rdvtofp27o3scimoy" style="color: black;">International Journal of Engineering Applied Sciences and Technology</a> </i> &nbsp;
From the results obtained from several studies on object detection and image classification using Convolutional Neural Networks (CNNs), it is possible to study the material classification of everyday objects  ...  One of the chief challenges faced today is determining the material category of a surface from an image.  ...  [10] "Data-augmentation" is very important to train the "neural networks" for "image classification".  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33564/ijeast.2020.v05i02.070">doi:10.33564/ijeast.2020.v05i02.070</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ijcwfdhbnnczbpqyp757vqussa">fatcat:ijcwfdhbnnczbpqyp757vqussa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201019072406/https://www.ijeast.com/papers/428-434,Tesma502,IJEAST.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/4c/5f/4c5fc24fdb39d449c4210bbbfc322cc50b9813cb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33564/ijeast.2020.v05i02.070"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Deep learning in remote sensing scene classification: a data augmentation enhanced convolutional neural network framework

Xingrui Yu, Xiaomin Wu, Chunbo Luo, Peng Ren
<span title="2017-05-05">2017</span> <i title="Informa UK Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/voeo5q267nh2xihjcy6e72jkqe" style="color: black;">GIScience &amp; Remote Sensing</a> </i> &nbsp;
enhanced datasets to train a deep convolutional neural network (CNN) that achieves state-of-the-art scene classification performance.  ...  Specifically, we propose to enhance any original dataset by applying three operations: flip, translation and rotation to generate augmented data, and use the augmented dataset to train and obtain a more  ...  Experimental Evaluations In this section, we empirically evaluate our strategy for training a deep convolutional neural network for scene classification based on data augmentation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/15481603.2017.1323377">doi:10.1080/15481603.2017.1323377</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fm54suan5nhhthnvi4nu2qebvu">fatcat:fm54suan5nhhthnvi4nu2qebvu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200311045642/https://ore.exeter.ac.uk/repository/bitstream/handle/10871/35130/GISience_RS_Revision.pdf;jsessionid=15617B90480BFC01CD04BD17A4C40B16?sequence=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/ca/67/ca67a30b7400796b496a986fd10966278e87b1b2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1080/15481603.2017.1323377"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> tandfonline.com </button> </a>

Automatic Ship Classification from Optical Aerial Images with Convolutional Neural Networks

Antonio-Javier Gallego, Antonio Pertusa, Pablo Gil
<span title="2018-03-24">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
A new dataset (named MASATI) composed of aerial imagery with more than 6000 samples has also been created to train and evaluate our architecture.  ...  The proposed architecture is based on Convolutional Neural Networks (CNN), and it combines neural codes extracted from a CNN with a k-Nearest Neighbor method so as to improve performance.  ...  The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs10040511">doi:10.3390/rs10040511</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/o6o7ldkgjbfspjjf525bmfkgou">fatcat:o6o7ldkgjbfspjjf525bmfkgou</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180722183441/https://rua.ua.es/dspace/bitstream/10045/74529/1/2018_Gallego_etal_RemoteSensing.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/95/66/9566fdf02af73b5d495005e2ea7fddeb770dca47.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs10040511"> <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>

Classification-driven Single Image Dehazing [article]

Yanting Pei, Yaping Huang, Xingyuan Zhang
<span title="2019-11-21">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We conduct comprehensive experiments on two challenging benchmark datasets for fine-grained and object classification: CUB-200-2011 and Caltech-256.  ...  In this paper, we investigate a new point of view in addressing this problem.  ...  [9] propose a multi-scale deep neural network for haze removal, and the network consists of a coarse-scale sub-network for a holistic transmission map and a fine-scale sub-network for local refinement  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1911.09389v1">arXiv:1911.09389v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/snbtcfcycfhgbcsegibhtjnu74">fatcat:snbtcfcycfhgbcsegibhtjnu74</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200911130500/https://arxiv.org/pdf/1911.09389v1.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/ee/8b/ee8b65e74016d6752b9bc5ba52981b3528ac24c4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1911.09389v1" 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>

Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks

Salman Khaleghian, Habib Ullah, Thomas Kræmer, Nick Hughes, Torbjørn Eltoft, Andrea Marinoni
<span title="">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
We explore new and existing convolutional neural network (CNN) architectures for sea ice classification using Sentinel-1 (S1) synthetic aperture radar (SAR) data by investigating two key challenges: binary  ...  sea ice versus open-water classification, and a multi-class sea ice type classification.  ...  Abbreviations We provide the abbreviations used in the paper in this part SAR Synthetic aperture radar LSTM Long short term memory DNNs Deep neural networks FCN Fully convolutional networks PCA Principal  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs13091734">doi:10.3390/rs13091734</a> <a target="_blank" rel="external noopener" href="https://doaj.org/article/9a74355e7f4f4db3be867fb1ab67f8b6">doaj:9a74355e7f4f4db3be867fb1ab67f8b6</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bkmkytrr5zhgbm3phngbqokmki">fatcat:bkmkytrr5zhgbm3phngbqokmki</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210715202025/https://res.mdpi.com/d_attachment/remotesensing/remotesensing-13-01734/article_deploy/remotesensing-13-01734-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/fe/3c/fe3c30aee573ef8776801258d868e93324628a7c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs13091734"> <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>

Deep learning for time series classification [article]

Hassan Ismail Fawaz
<span title="2020-10-01">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The main objective of this thesis was to study and develop deep neural networks specifically constructed for the classification of time series data.  ...  Subsequently, we made numerous contributions in this area, notably in the context of transfer learning, data augmentation, ensembling and adversarial attacks.  ...  FIGURE 2 . 9 : 29 Ensemble of deep convolutional neural networks for time series classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2010.00567v1">arXiv:2010.00567v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6u4naewelzhdvmypxzdwxww5du">fatcat:6u4naewelzhdvmypxzdwxww5du</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201003200215/https://arxiv.org/pdf/2010.00567v1.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] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2010.00567v1" 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>

Urban Intersection Classification: A Comparative Analysis

Augusto Luis Ballardini, Álvaro Hernández Saz, Sandra Carrasco Limeros, Javier Lorenzo, Ignacio Parra Alonso, Noelia Hernández Parra, Iván García Daza, Miguel Ángel Sotelo
<span title="2021-09-18">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Due to the scarcity of training data, a new dataset is created by performing data augmentation from real-world data through a Generative Adversarial Network (GAN) to increase generalizability as well as  ...  Different methodologies aimed at classifying intersection geometries have been assessed to provide a comprehensive evaluation of state-of-the-art techniques based on Deep Neural Network (DNN) approaches  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21186269">doi:10.3390/s21186269</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34577480">pmid:34577480</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8473311/">pmcid:PMC8473311</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/inhq2fo7urhwpk6t3643guoptu">fatcat:inhq2fo7urhwpk6t3643guoptu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211001191306/https://mdpi-res.com/d_attachment/sensors/sensors-21-06269/article_deploy/sensors-21-06269-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/16/82/1682aa18073c072eb54dceb2a6b47f01bd5881db.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21186269"> <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> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473311" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Intelligent Traffic Monitoring Systems for Vehicle Classification: A Survey [article]

Myounggyu Won
<span title="2019-10-10">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
It is one of the critical transportation infrastructures that transportation agencies invest a huge amount of money to collect and analyze the traffic data to better utilize the roadway systems, improve  ...  In this article, we present a review of state-of-the-art traffic monitoring systems focusing on the major functionality--vehicle classification.  ...  and convolutional neural network (CNN) [61] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1910.04656v1">arXiv:1910.04656v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/a4fquz53r5hjde5ypzpcmq727u">fatcat:a4fquz53r5hjde5ypzpcmq727u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200726222520/https://arxiv.org/pdf/1910.04656v1.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] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1910.04656v1" 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>

Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset [article]

Martin Mundt, Sagnik Majumder, Sreenivas Murali, Panagiotis Panetsos, Visvanathan Ramesh
<span title="2019-04-02">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We investigate and compare two reinforcement learning based meta-learning approaches, MetaQNN and efficient neural architecture search, to find suitable convolutional neural network architectures for this  ...  In this work we introduce the novel COncrete DEfect BRidge IMage dataset (CODEBRIM) for multi-target classification of five commonly appearing concrete defects.  ...  We further thank FADA-CATEC, Tobias Weis and Sumit Pai for their support in parts of the data acquisition and Hieu Pham for valuable discussion of ENAS hyper-parameters.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.08486v1">arXiv:1904.08486v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fnbtdw5g6jdg3bj55pad5afw3a">fatcat:fnbtdw5g6jdg3bj55pad5afw3a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200929214202/https://arxiv.org/pdf/1904.08486v1.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/27/ef/27eff988e11b1f4d1de782de5791c75e36af3ec2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.08486v1" 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>

Convolutional Neural Networks for Classification of Drones Using Radars

Divy Raval, Emily Hunter, Sinclair Hudson, Anthony Damini, Bhashyam Balaji
<span title="2021-12-15">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ycpqunwwuja6beynxtnfswzqgy" style="color: black;">Drones</a> </i> &nbsp;
We examine the data under X-band and W-band radar simulation scenarios and show that a CNN approach leads to an F1 score of 0.816±0.011 when trained on data with a signal-to-noise ratio (SNR) of 10 dB.  ...  In this paper, we apply convolutional neural networks (CNNs) to the Short-Time Fourier Transform (STFT) spectrograms of the simulated radar signals reflected from the drones.  ...  Acknowledgments: We would like to thank CANSOFCOM and the organizers of the Hack the North for the challenge.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/drones5040149">doi:10.3390/drones5040149</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6fsfvzyibrhmxow6cfizaqug2m">fatcat:6fsfvzyibrhmxow6cfizaqug2m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220505061115/https://mdpi-res.com/d_attachment/drones/drones-05-00149/article_deploy/drones-05-00149-v2.pdf?version=1639639885" 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/aa/b2/aab205547bf69e81b68e18da87714425a74117cb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/drones5040149"> <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>

Unsupervised classification of snowflake images using a generative adversarial network and K-medoids classification

Jussi Leinonen, Alexis Berne
<span title="2020-06-05">2020</span> <i title="Copernicus GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/e75narf6sndlrklma5bs5k6smm" style="color: black;">Atmospheric Measurement Techniques</a> </i> &nbsp;
We found that the classification scheme is able to separate the dataset into distinct classes, each characterized by a particular size, shape and texture of the snowflake image, providing signatures of  ...  An alternative is unsupervised classification, which seeks to divide a dataset into distinct classes without expert-provided labels.  ...  We thank Yves-Alain Roulet and Jacques Grandjean of MeteoSwiss for the MASC data from Davos, and Christophe Praz for assistance with processing the data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/amt-13-2949-2020">doi:10.5194/amt-13-2949-2020</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/invbtsij25e7xh63yqvgfjjtw4">fatcat:invbtsij25e7xh63yqvgfjjtw4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200606010744/https://www.atmos-meas-tech.net/13/2949/2020/amt-13-2949-2020.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/0d/7a/0d7a04829214e88d59537918e8039061a7028bb6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5194/amt-13-2949-2020"> <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 Concurrent and Hierarchy Target Learning Architecture for Classification in SAR Application

Mohamed Touafria, Qiang Yang
<span title="2018-09-24">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Through learning the hierarchy of features automatically from a massive amount of training data, learning networks such as Convolutional Neural Networks (CNN) has recently achieved state-of-the-art results  ...  To extract better features about SAR targets, and to obtain better accuracies, a new framework is proposed: First, three CNN models based on different convolution and pooling kernel sizes are proposed.  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s18103218">doi:10.3390/s18103218</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30249976">pmid:30249976</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6210434/">pmcid:PMC6210434</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3xli2jxxwfbdrgms74am3ukyye">fatcat:3xli2jxxwfbdrgms74am3ukyye</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190503235246/https://res.mdpi.com/sensors/sensors-18-03218/article_deploy/sensors-18-03218-v3.pdf?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/66/52/6652ee24a7632254645d0ed5847f58a0e3f8706b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s18103218"> <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> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210434" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>
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