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Human Experts Fusion For Image Classification

Arnaud MARTIN, Christophe OSSWALD
<span title="2008-06-11">2008</span> <i title="Zenodo"> Zenodo </i> &nbsp;
In image classification, merging the opinion of several human experts is very important for different tasks such as the evaluation or the training.  ...  The considered unit for the classification, a small tile of the image, can contain one or more kind of the considered classes given by the experts.  ...  Introduction Fusing the opinion of several human experts, also known as the experts fusion problem, is an important question in the image classication eld and very few studied.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.32219">doi:10.5281/zenodo.32219</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/emvopfvx75cunplntk4ogb65qa">fatcat:emvopfvx75cunplntk4ogb65qa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321023652/http://www.arnaud.martin.free.fr/publi/MARTIN_06b.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/b2/98/b29874fdc23245212c5d6828470f20211f75d332.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.32219"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

Human Expert Fusion for Image Classification

Arnaud Martin, Christophe Osswald
<span title="">2006</span> <i title="Procon, Ltd."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tvg6uqc2trf33c7i7fjhmumtru" style="color: black;">Information &amp; Security An International Journal</a> </i> &nbsp;
In image classification, merging the opinion of several human experts is very important for different tasks such as the evaluation or the training.  ...  The considered unit for the classification, a small tile of the image, can contain one or more kind of the considered classes given by the experts.  ...  Introduction Fusing the opinion of several human experts, also known as the experts fusion problem, is an important question in the image classification field and very few studied.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11610/isij.2006">doi:10.11610/isij.2006</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/m4sft2hnwjhfdjfyuontq763xa">fatcat:m4sft2hnwjhfdjfyuontq763xa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721140402/http://procon.bg/system/files/20.06_ArnaudMartin.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/d8/9e/d89e8e60583899850b4244a177003004b2bae478.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11610/isij.2006"> <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>

Human expert fusion for image classification [article]

Arnaud Martin
<span title="2008-06-11">2008</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In image classification, merging the opinion of several human experts is very important for different tasks such as the evaluation or the training.  ...  The considered unit for the classification, a small tile of the image, can contain one or more kind of the considered classes given by the experts.  ...  Introduction Fusing the opinion of several human experts, also known as the experts fusion problem, is an important question in the image classification field and very few studied.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/0806.1798v1">arXiv:0806.1798v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lvi2dwjqdnfxbghmfvggj5atcy">fatcat:lvi2dwjqdnfxbghmfvggj5atcy</a> </span>
<a target="_blank" rel="noopener" href="https://archive.org/download/arxiv-0806.1798/0806.1798.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> File Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/0806.1798v1" 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>

Fusion for Evaluation of Image Classification in Uncertain Environments [article]

Arnaud Martin
<span title="2008-05-26">2008</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We present the results of this method on a fusion of classifiers of sonar images for a seabed characterization.  ...  We present in this article a new evaluation method for classification and segmentation of textured images in uncertain environments.  ...  For instance, with satellite or sonar images, human experts must be able to classify the types of soils present in the images.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/0805.3935v1">arXiv:0805.3935v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qogriw5fyvd2zlmiqtbifwwb4y">fatcat:qogriw5fyvd2zlmiqtbifwwb4y</a> </span>
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A Fusion Approach for Image Triage using Single Trial ERP Detection

Yonghong Huang, Deniz Erdogmus, Santosh Mathan, Misha Pavel
<span title="">2007</span> <i title="IEEE"> 2007 3rd International IEEE/EMBS Conference on Neural Engineering </i> &nbsp;
An experimental evaluation of the method was conducted using trained human experts in the paradigm of finding target objects in broad area aerial images.  ...  This paper addresses the problem of conducting visual target search on a large set of images.  ...  It has been approved for Public Release, Distribution Unlimited. Some of the data used in the experiments were collected at the Honeywell Human-Centered Systems Laboratory (Minneapolis, MN).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cne.2007.369712">doi:10.1109/cne.2007.369712</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yvlrz5bmovb4tnar4m6gxot43q">fatcat:yvlrz5bmovb4tnar4m6gxot43q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20110623144240/http://indigo.ece.neu.edu/~erdogmus/publications/C115_NER2007_RSVPerp_Catherine.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/14/f0/14f0712e67ab6814f6f3ad0c3393de7da6c1f096.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cne.2007.369712"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Classifier fusion for outdoor obstacle detection

C.S. Dima, N. Vandapel, M. Hebert
<span title="">2004</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nytnrt3gtzbixld5r6a4talbky" style="color: black;">IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA &#39;04. 2004</a> </i> &nbsp;
This paper describes an approach for using several levels of data fusion in the domain of autonomous off-road navigation.  ...  We are focusing on outdoor obstacle detection, and we present techniques that leverage on data fusion and machine learning for increasing the reliability of obstacle detection systems.  ...  Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/robot.2004.1307225">doi:10.1109/robot.2004.1307225</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icra/DimaVH04.html">dblp:conf/icra/DimaVH04</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oba3d63h7vfa3nbs77wykgoeoi">fatcat:oba3d63h7vfa3nbs77wykgoeoi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150922082115/http://www.ri.cmu.edu:80/pub_files/pub4/dima_cristian_2004_1/dima_cristian_2004_1.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/65/2c/652c96b152d498c81a997d5818a502cab686ef17.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/robot.2004.1307225"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Extraction and Application of Expert Priors to Combine Multiple Segmentations of Human Brain Tissue [chapter]

Torsten Rohlfing, Daniel B. Russakoff, Calvin R. Maurer
<span title="">2003</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;
This paper evaluates strategies to combine multiple segmentations of the same image, generated for example by different segmentation methods or by different human experts.  ...  A validation study using the MNI BrainWeb phantom shows that decision fusion based on the two EM methods consistently outperforms label averaging.  ...  DBR was supported by the Interdisciplinary Initiatives Program, which is part of the Bio-X Program at Stanford University, under the grant "Image-Guided Radiosurgery for the Spine and Lungs."  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-39903-2_71">doi:10.1007/978-3-540-39903-2_71</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/snpuyic4t5aolfw262iutne6du">fatcat:snpuyic4t5aolfw262iutne6du</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190503193939/https://link.springer.com/content/pdf/10.1007%2F978-3-540-39903-2_71.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/c4/80/c480aadb1a7d9704e6db65154158806cde37d136.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-39903-2_71"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

MEG: Multi-Expert Gender Classification from Face Images in a Demographics-Balanced Dataset [chapter]

Modesto Castrillón-Santana, Maria De Marsico, Michele Nappi, Daniel Riccio
<span title="">2015</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this paper we focus on gender classification from face images, which is still a challenging task in unrestricted scenarios.  ...  As expected, feature level fusion achieves an often better classification performance but it is also quite computationally expensive.  ...  experts E i for a given image I k in the new compound vector.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-23231-7_2">doi:10.1007/978-3-319-23231-7_2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oosj3nvkzba7hmgl6tgagrifj4">fatcat:oosj3nvkzba7hmgl6tgagrifj4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721203238/http://cris.ulpgc.es/jspui/bitstream/10553/20097/5/C095-ICIAP15_preprint.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/17/6f/176f26a6a8e04567ea71677b99e9818f8a8819d0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-23231-7_2"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Focal Liver Lesion Detection in Ultrasound Image Using Deep Feature Fusions and Super Resolution

Rafid Mostafiz, Mohammad Motiur Rahman, A. K. M. Kamrul Islam, Saeid Belkasim
<span title="2020-07-09">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tjwucdga6zfftlebfsmbvxjiyy" style="color: black;">Machine Learning and Knowledge Extraction</a> </i> &nbsp;
ultrasound image patches.  ...  To dig for more potential information, a learnable super-resolution (SR) is embedded into the deep CNN.  ...  (b,c) Misdetection by human expert and proposed approach. end if end if end for do Mach. Learn. Knowl.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/make2030010">doi:10.3390/make2030010</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bsw7jic7gnax5fjsf64xgtmr6y">fatcat:bsw7jic7gnax5fjsf64xgtmr6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200710014718/https://res.mdpi.com/d_attachment/make/make-02-00010/article_deploy/make-02-00010.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/61/45/61455215495d4f8a9158e623b62748e9bead8e48.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/make2030010"> <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>

Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification [article]

Arnaud Martin
<span title="2008-06-12">2008</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms.  ...  However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict.  ...  Therefore, sonar images have a lot of imperfections such as imprecision and uncertainty; thus sediment classification on sonar images is a difficult problem even for human experts.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/0806.2007v1">arXiv:0806.2007v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/v7dza5ooorb3nevcy2yrlwpt4e">fatcat:v7dza5ooorb3nevcy2yrlwpt4e</a> </span>
<a target="_blank" rel="noopener" href="https://archive.org/download/arxiv-0806.2007/0806.2007.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> File Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/0806.2007v1" 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>

Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification

Arnaud Martin, Christophe Osswald
<span title="">2008</span> <i title="IEEE"> 2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications </i> &nbsp;
In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms.  ...  However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict.  ...  Therefore, sonar images have a lot of imperfections such as imprecision and uncertainty; thus sediment classification on sonar images is a difficult problem even for human experts.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ictta.2008.4530035">doi:10.1109/ictta.2008.4530035</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/va2z2ciiiba3bipnl2ujdt32mu">fatcat:va2z2ciiiba3bipnl2ujdt32mu</a> </span>
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Gastrointestinal polyp classification through empirical mode decomposition and neural features

Rafid Mostafiz, Mohammad Motiur Rahman, Mohammad Shorif Uddin
<span title="2020-05-30">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wxtpc7l3qzds3ojx4uwv4dvlr4" style="color: black;">SN Applied Sciences</a> </i> &nbsp;
Moreover, it shows potentiality in precisely classifying some challenging polyps even though these are somehow confusing for human experts.  ...  The polyp-type classification is performed by a multiclass support vector machine from feature-fusion of bi-dimensional empirical mode decomposition (BEMD) and convolutional neural network (CNN).  ...  Proper acknowledgments with citation guidelines are maintained for the use of these datasets.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s42452-020-2944-4">doi:10.1007/s42452-020-2944-4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bfslqyje3rcejorakayackldhe">fatcat:bfslqyje3rcejorakayackldhe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201107210538/https://link.springer.com/content/pdf/10.1007/s42452-020-2944-4.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/11/ac/11ac7b5a4662eefc61ea6e2d0444eeb61b4f42bd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s42452-020-2944-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

DRDF: Determining the Importance of Different Multimodal Information with Dual-Router Dynamic Framework [article]

Haiwen Hong, Xuan Jin, Yin Zhang, Yunqing Hu, Jingfeng Zhang, Yuan He, Hui Xue
<span title="2021-07-21">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Based on the result of the determination, MWF-Layer generates fused weights for the fusion of experts. Experts are model backbones that match the current task.  ...  Dynamic Framework (DRDF), consisting of Dual-Router, MWF-Layer, experts and expert fusion unit.  ...  Dual-Router has actually made a rough classification of the input case, and the experts fusion according to the fused weights is a fine-grained classification for the input cases.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2107.09909v1">arXiv:2107.09909v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bo2rtjg77vadfodfmscp42dyra">fatcat:bo2rtjg77vadfodfmscp42dyra</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210723031610/https://arxiv.org/pdf/2107.09909v1.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/2b/ca/2bcabee7e214aff6d766ea9a6c49e4a67b902d8d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2107.09909v1" 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>

Remote Sensing of Mangrove Wetlands Identification

Song Xue Fei, Cui Hai Shan, Guo Zhi Hua
<span title="">2011</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2i4dodta3jfcjf5zgk6skuuhwm" style="color: black;">Procedia Environmental Sciences</a> </i> &nbsp;
Mangrove wetland has become the important and hot object for wetland research in recent years.  ...  This paper introduces the source of data of the mangrove remote sensing recognition technology processing, classification method and feature extraction.We also analyze the existings weakness, finally we  ...  *CUI Hai Shan is the author for corresponding.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.proenv.2011.09.357">doi:10.1016/j.proenv.2011.09.357</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cln2nqzjq5avzaooyeh36zrm3u">fatcat:cln2nqzjq5avzaooyeh36zrm3u</a> </span>
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Solving the Families In the Wild Kinship Verification Challenge by Program Synthesis [article]

Junyi Huang, Maxwell Benjamin Strome, Ian Jenkins, Parker Williams, Bo Feng, Yaning Wang, Roman Wang, Vaibhav Bagri, Newman Cheng, Iddo Drori
<span title="2021-12-02">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We ensemble models written by both human experts and a foundation model, OpenAI Codex, trained on text and code.  ...  We use Codex to generate model variants, and also demonstrate its ability to generate entire running programs for kinship verification tasks of specific relationships.  ...  The task of kinship recognition was initially tackled over a decade ago [7] by extracting low-level image features for classification.  ... 
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