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Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery

Changwon Suh, Clyde Fare, James A. Warren, Edward O. Pyzer-Knapp
<span title="2020-04-21">2020</span> <i title="Annual Reviews"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ixr4m4evbndnnhg74jqrjqzsfq" style="color: black;">Annual review of materials research (Print)</a> </i> &nbsp;
Additionally, we discuss a clear path toward a future where data-driven approaches to materials discovery and design are standard practice.  ...  Expected final online publication date for the Annual Review of Materials Research, Volume 50 is July 1, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.  ...  Multitask learning, where multiple chemical properties are learned at once, allows for the generation of more general transferable fingerprints.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1146/annurev-matsci-082019-105100">doi:10.1146/annurev-matsci-082019-105100</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dyxljg2mu5grzlakeeatvyymd4">fatcat:dyxljg2mu5grzlakeeatvyymd4</a> </span>
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Cycle-consistent generative adversarial neural networks based low quality fingerprint enhancement

Dogus Karabulut, Pavlo Tertychnyi, Hasan Sait Arslan, Cagri Ozcinar, Kamal Nasrollahi, Joan Valls, Joan Vilaseca, Thomas B. Moeslund, Gholamreza Anbarjafari
<span title="2020-03-06">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7inqmh346zfjjizjyieh7ijtma" style="color: black;">Multimedia tools and applications</a> </i> &nbsp;
For the evaluation of the proposed enhancement technique, we use VGG16 based convolutional neural network to assess the percentage of enhanced fingerprint images which are labelled correctly as undistorted  ...  Distortions such as dryness, wetness, blurriness, physical damages and presence of dots in fingerprints are a detriment to a good analysis of them.  ...  [39] developed a threshold fast Fourier transform approach to simultaneously smooth and enhance poor quality images.  ... 
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2020 Index IEEE Transactions on Information Forensics and Security Vol. 15

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xqa4uhvxwvgsbdpllabnuanz6e" style="color: black;">IEEE Transactions on Information Forensics and Security</a> </i> &nbsp;
., +, TIFS 2020 753-766 AReN: A Deep Learning Approach for Sound Event Recognition Using a Brain Inspired Representation.  ...  ., +, TIFS 2020 500-511 Time-frequency analysis AReN: A Deep Learning Approach for Sound Event Recognition Using a Brain Inspired Representation.  ...  G Gait analysis Deep Learning-Based Gait Recognition Using Smartphones in the Wild.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tifs.2021.3053735">doi:10.1109/tifs.2021.3053735</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eforexmnczeqzdj3sc2j4yoige">fatcat:eforexmnczeqzdj3sc2j4yoige</a> </span>
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Extracting possibly representative COVID-19 Biomarkers from X-Ray images with Deep Learning approach and image data related to Pulmonary Diseases [article]

Ioannis D. Apostolopoulos, Sokratis Aznaouridis, Mpesiana Tzani
<span title="2020-04-06">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Deep Learning has proven to be a remarkable method to extract massive high-dimensional features from medical images.  ...  A large-scale dataset of 3905 X-Ray images, corresponding to 6 diseases is utilized for training MobileNet v2, which has been proven to achieve remarkable results in related tasks.  ...  Deep Learning is a learning method wherein deep Convolutional Neural Networks (CNN) are utilized for automatic mass feature extraction, achieved by the process called convolution [5] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2004.00338v2">arXiv:2004.00338v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7ffby6o6nbenfb24vop4w2sapi">fatcat:7ffby6o6nbenfb24vop4w2sapi</a> </span>
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2020 Index IEEE Signal Processing Letters Vol. 27

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/msfmoh6v7bdk7lrsmtbklto74i" style="color: black;">IEEE Signal Processing Letters</a> </i> &nbsp;
., +, LSP 2020 950-954 Learning Unbiased Zero-Shot Semantic Segmentation Networks Via Transductive Transfer.  ...  ., +, LSP 2020 660-664 On Security Enhancement of Steganography via Generative Adversarial Image.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/lsp.2021.3055468">doi:10.1109/lsp.2021.3055468</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wfdtkv6fmngihjdqultujzv4by">fatcat:wfdtkv6fmngihjdqultujzv4by</a> </span>
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Front Matter: Volume 11430

Zhenbing Liu, Jayaram K. Udupa, Nong Sang, Yuehuan Wang
<span title="2020-02-14">2020</span> <i title="SPIE"> MIPPR 2019: Pattern Recognition and Computer Vision </i> &nbsp;
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  A unique citation identifier (CID) number is assigned to each article at the time of publication.  ...  [11430-105] 11430 22 A novel neural network approach for error transfer analysis in electronic instrument transformer [11430-106] 11430 23 Large-scale book page retrieval by deep hashing networks  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2565844">doi:10.1117/12.2565844</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kapfwn4xajdt3jzin3mks33oam">fatcat:kapfwn4xajdt3jzin3mks33oam</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716092653/https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11430/1143001/Front-Matter-Volume-11430/10.1117/12.2565844.pdf?SSO=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/73/d9/73d92ebce539913c5dc15f7fd0bd9fad883f945f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2565844"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

2021 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 43

<span title="">2022</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3px634ph3vhrtmtuip6xznraqi" style="color: black;">IEEE Transactions on Pattern Analysis and Machine Intelligence</a> </i> &nbsp;
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TPAMI July 2021 2373-2387 Pattern of Local Gravitational Force (PLGF): A Novel Local Image Descriptor.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tpami.2021.3126216">doi:10.1109/tpami.2021.3126216</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h6bdbf2tdngefjgj76cudpoyia">fatcat:h6bdbf2tdngefjgj76cudpoyia</a> </span>
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Extracting Possibly Representative COVID-19 Biomarkers from X-ray Images with Deep Learning Approach and Image Data Related to Pulmonary Diseases

Ioannis D. Apostolopoulos, Sokratis I. Aznaouridis, Mpesiana A. Tzani
<span title="2020-05-14">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jkyhfidlx5ggphgj6fhra2yyzu" style="color: black;">Journal of Medical and Biological Engineering</a> </i> &nbsp;
Deep Learning has proven to be a remarkable method to extract massive high-dimensional features from medical images.  ...  A large-scale dataset of 3905 X-ray images, corresponding to 6 diseases, is utilized for training MobileNet v2, which has been proven to achieve excellent results in related tasks.  ...  Deep Learning for pattern recogtition in images is a learning method, wherein deep Convolutional Neural Networks (CNN) are utilized for automatic mass feature extraction, achieved by the process called  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s40846-020-00529-4">doi:10.1007/s40846-020-00529-4</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32412551">pmid:32412551</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7221329/">pmcid:PMC7221329</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/onl6pt3s25godjd6gsjula7qsi">fatcat:onl6pt3s25godjd6gsjula7qsi</a> </span>
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Biometric Presentation Attack Detection: Beyond the Visible Spectrum

Ruben Tolosana, Marta Gomez-Barrero, Christoph Busch, Javier Ortega-Garcia
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xqa4uhvxwvgsbdpllabnuanz6e" style="color: black;">IEEE Transactions on Information Forensics and Security</a> </i> &nbsp;
i) an in-depth analysis of several state-of-theart techniques based on both handcrafted and deep learning features.  ...  In this context, we present a novel fingerprint presentation attack detection (PAD) scheme based on i) a new capture device able to acquire images within the short wave infrared (SWIR) spectrum, and i  ...  Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein. This work was carried out during an internship of R.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tifs.2019.2934867">doi:10.1109/tifs.2019.2934867</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q3vzyshn2bepdo4nd2dgb2doa4">fatcat:q3vzyshn2bepdo4nd2dgb2doa4</a> </span>
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Advances in Deep Learning-Based Medical Image Analysis

Xiaoqing Liu, Kunlun Gao, Bo Liu, Chengwei Pan, Kongming Liang, Lifeng Yan, Jiechao Ma, Fujin He, Shu Zhang, Siyuan Pan, Yizhou Yu
<span title="2021-06-16">2021</span> <i title="American Association for the Advancement of Science (AAAS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lrzj2y4osvcbvdtsltx6elkmuq" style="color: black;">Health Data Science</a> </i> &nbsp;
With the booming growth of artificial intelligence (AI), especially the recent advancements of deep learning, utilizing advanced deep learning-based methods for medical image analysis has become an active  ...  This paper reviewed the recent progress of deep learning research in medical image analysis and clinical applications.  ...  Segmentation of Cardiac Structures. Vigneault et al. [82] presented a novel deep CNN architecture called Ω-Net for fully automatic whole-heart segmentation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.34133/2021/8786793">doi:10.34133/2021/8786793</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/d6nkb4yoxrcgni4y5owju5pnh4">fatcat:d6nkb4yoxrcgni4y5owju5pnh4</a> </span>
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Face Verification with Disguise Variations via Deep Disguise Recognizer

Naman Kohli, Daksha Yadav, Afzel Noore
<span title="">2018</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</a> </i> &nbsp;
In this paper, we utilize deep learning based transfer learning approach for face verification with disguise variations.  ...  The training for the Inception-ResNet model is performed using a large-scale face database which is followed by inductive transfer learning to mitigate the impact of facial disguises.  ...  Acknowledgment The authors gratefully acknowledge the support of NVIDIA Corporation with the donation of the Tesla K40 and Titan X Pascal GPUs used for this research.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvprw.2018.00010">doi:10.1109/cvprw.2018.00010</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/KohliYN18.html">dblp:conf/cvpr/KohliYN18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dxarwxbbsnhvvmh4lcwftcg62q">fatcat:dxarwxbbsnhvvmh4lcwftcg62q</a> </span>
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Content

<span title="2021-12-01">2021</span> <i title="IEEE"> 2021 IEEE 12th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON) </i> &nbsp;
Supervised Machine Learning Based 04.1 1570774294 Probabilistic Approach to Play Tic-Tac-Toe 0116 1570771601 A Novel Partitioning Scheme for Partial Transmit 04.2  ...  Compute-Intensive Applications 0619 1570768332 SESSION 19: MACHINE LEARNING 19.1 1570775816 Diabetic Retinopathy Classification With Pre-Trained Image Enhancement  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/uemcon53757.2021.9666620">doi:10.1109/uemcon53757.2021.9666620</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kf4age44ubbnflwwp3ldepum3e">fatcat:kf4age44ubbnflwwp3ldepum3e</a> </span>
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DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection [article]

Ruben Tolosana, Ruben Vera-Rodriguez, Julian Fierrez, Aythami Morales, Javier Ortega-Garcia
<span title="2020-06-18">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This survey provides a thorough review of techniques for manipulating face images including DeepFake methods, and methods to detect such manipulations.  ...  The free access to large-scale public databases, together with the fast progress of deep learning techniques, in particular Generative Adversarial Networks, have led to the generation of very realistic  ...  ACKNOWLEDGMENTS This work has been supported by projects: PRIMA (H2020-MSCA-ITN-2019-860315), TRESPASS-ETN (H2020-MSCA-ITN-2019-860813), BIBECA (MINECO/FEDER RTI2018-101248-B-I00), Bio-Guard (Ayudas Fundación BBVA a  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2001.00179v3">arXiv:2001.00179v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tq4sqedsgve23pwm66qidbzgt4">fatcat:tq4sqedsgve23pwm66qidbzgt4</a> </span>
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2020 Index IEEE Transactions on Image Processing Vol. 29

<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dhlhr4jqkbcmdbua2ca45o7kru" style="color: black;">IEEE Transactions on Image Processing</a> </i> &nbsp;
., +, TIP 2020 6507-6522 Biomedical optical imaging A Novel Deep Learning Pipeline for Retinal Vessel Detection In Fluorescein Angiography.  ...  ., +, TIP 2020 3927-3940 Efficient Evaluation of Image Quality via Deep-Learning Approximation of Perceptual Metrics.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tip.2020.3046056">doi:10.1109/tip.2020.3046056</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/24m6k2elprf2nfmucbjzhvzk3m">fatcat:24m6k2elprf2nfmucbjzhvzk3m</a> </span>
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Survey on Deep Multi-modal Data Analytics: Collaboration, Rivalry and Fusion [article]

Yang Wang
<span title="2020-06-15">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Recently, deep neural networks have exhibited as a powerful architecture to well capture the nonlinear distribution of high-dimensional multimedia data, so naturally does for multi-modal data.  ...  In this paper, we provide a substantial overview of the existing state-of-the-arts on the filed of multi-modal data analytics from shallow to deep spaces.  ...  [37] proposed a novel cross-modal method which can transfer supervision from labeled RGB images to unlabeled depth and optical flow images.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.08159v1">arXiv:2006.08159v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/g4467zmutndglmy35n3eyfwxku">fatcat:g4467zmutndglmy35n3eyfwxku</a> </span>
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