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Neural Object Recognition by Hierarchical Learning and Extraction of Essential Shapes [chapter]

Daniel Oberhoff, Marina Kolesnik
<i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zpbe6fclhzdx3gvkyxg6dnmy5i" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
We present a hierarchical system for object recognition that models neural mechanisms of visual processing identified in the mammalian ventral stream.  ...  We also present a neural mechanism for back projection of the learned image patterns down the hierarchical layers.  ...  Conclusion We have described the hierarchical learning system for shape based object recognition inspired by neurophysiological evidence on ventral stream processing in the mammalian brain.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-75555-5_27">doi:10.1007/978-3-540-75555-5_27</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/bvai/OberhoffK07.html">dblp:conf/bvai/OberhoffK07</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hs2kob6t2remjdgk2qt4juxogy">fatcat:hs2kob6t2remjdgk2qt4juxogy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829161949/http://mitarbeiter.fit.fraunhofer.de/~kolesnik/papers/pdf/bvai2007.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/9f/20/9f206677db38fac42668d590027a8c010b485557.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-75555-5_27"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Face Recognition Based on Deep Learning [chapter]

Weihong Wang, Jie Yang, Jianwei Xiao, Sheng Li, Dixin Zhou
<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;
The conventional approach employs Histogram of Gradient (HOG) algorithm to extract features and utilizes a multi-class Support Vector Machine (SVM) classifier to train and learn the classification.  ...  In order to verify the performance of the proposed approach, it is compared with a conventional face recognition method by using various comprehensive datasets.  ...  Deep learning is essentially a multi-layer artificial neural network-based machine learning technique.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-15554-8_73">doi:10.1007/978-3-319-15554-8_73</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wxbollwlwve6rjrepkqfoyhm34">fatcat:wxbollwlwve6rjrepkqfoyhm34</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200326103131/https://dergipark.org.tr/en/download/article-file/758943" 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/44/bc/44bcdeb9f5e432f5b8b48ef93d4623683d6cff25.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-15554-8_73"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

View-independent recognition of grasping actions with a cortex-inspired model

Falk Fleischer, Antonino Casile, Martin A. Giese
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/p2nw3ufilvbknotfq56xtvnhtq" style="color: black;">2009 9th IEEE-RAS International Conference on Humanoid Robots</a> </i> &nbsp;
However, this recognition task is difficult and requires the capturing of the details of effector and goal object under a wide range of image transformations, such as view or position changes.  ...  To recognize how people interact with objects is essential for humans and artificial systems like robots.  ...  View-dependent shape recognition The first component of the developed system is formed by a hierarchical neural architecture for shape recognition similar to [35, 27] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ichr.2009.5379524">doi:10.1109/ichr.2009.5379524</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/humanoids/FleischerCG09.html">dblp:conf/humanoids/FleischerCG09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ibrco2nllrhybngg2nlge2rcju">fatcat:ibrco2nllrhybngg2nlge2rcju</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811043750/http://www.compsens.uni-tuebingen.de/joomla/administrator/components/com_jresearch/files/publications/FleischerIEEE2012.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/da/ea/daeab44bf8c253aca55f8a80be3d9a8f503bd392.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ichr.2009.5379524"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Hierarchical Neural Learning for Object Recognition

Daniel Oberhoff, Marina Kolesnik, Marc M. Van Hulle
<span title="">2007</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zcexqu347zfhje6pnlbwdfbcaa" style="color: black;">Machine Learning for Signal Processing</a> </i> &nbsp;
We present a neural-based learning system for object recognition in still gray-scale images.  ...  On the highest level of the hierarchy, the decision on the class of an object is taken by a linear classifier depending solely on the object's shape.  ...  CONCLUSIONS AND FUTURE WORK We have presented a neural hierarchical system for shift invariant object recognition employing unsupervised learning to generate features to classify object shapes.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/mlsp.2007.4414334">doi:10.1109/mlsp.2007.4414334</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ddnyullmzfbz7avmpbdpbk4wom">fatcat:ddnyullmzfbz7avmpbdpbk4wom</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170812011144/http://gbiomed.kuleuven.be/english/research/50000666/50000669/50488669/neuro_research/neuro_research_mvanhulle/comp_pdf/MLSP07_2.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/5a/6f/5a6f17ae00ed83c6f4e54632c63c6cf5488c309f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/mlsp.2007.4414334"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Using Derived Kernel as a new Method for Recognition a Similarity Learning

<span title="2020-02-29">2020</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h673cvfolnhl3mnbjxkhtxdtg4" style="color: black;">International Journal of Engineering and Advanced Technology</a> </i> &nbsp;
A new technique for feature withdrawal by neural response is going to be familiarized in this research work by merging an entropy measure with Squared Pearson correlation Coefficient (SPCC) method.  ...  The process of choosing effective models on the basis of entropy measures was proposed further to enhance the ability to select templates.  ...  Another technique is suggested in [24, 25] to a feature extraction scheme using neural response by linking the hierarchical architectures with the sparse coding.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.c5705.029320">doi:10.35940/ijeat.c5705.029320</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q5h6wocmgvcxfbsxqcwp4r3pfa">fatcat:q5h6wocmgvcxfbsxqcwp4r3pfa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200308140228/https://www.ijeat.org/wp-content/uploads/papers/v9i3/C5705029320.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 noreferrer" href="https://doi.org/10.35940/ijeat.c5705.029320"> <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>

Multipath Convolutional-Recursive Neural Networks for Object Recognition [chapter]

Xiangyang Li, Shuqiang Jiang, Xinhang Song, Luis Herranz, Zhiping Shi
<span title="">2014</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kss7mrolvja63k4rmix3iynkzi" style="color: black;">IFIP Advances in Information and Communication Technology</a> </i> &nbsp;
Extracting good representations from images is essential for many computer vision tasks.  ...  and recursive neural networks (CNNs and RNNs).  ...  The final layer of each path is a feature vector for the whole image. All the features are then concatenated and used by a svm classifier for object recognition.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-662-44980-6_30">doi:10.1007/978-3-662-44980-6_30</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/s24t35huifdyxcsqoctmef3oom">fatcat:s24t35huifdyxcsqoctmef3oom</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200322132633/https://rd.springer.com/content/pdf/10.1007%2F978-3-662-44980-6_30.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/76/11/7611586e560e0652369b0506206e76c9149e6054.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-662-44980-6_30"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Multi-Model CNN-RNN-LSTM Based Fruit Recognition and Classification

Harmandeep Singh Gill, Osamah Ibrahim Khalaf, Youseef Alotaibi, Saleh Alghamdi, Fawaz Alassery
<span title="">2022</span> <i title="Computers, Materials and Continua (Tech Science Press)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a6m5ovtnq5h6bb2dcb357moo4a" style="color: black;">Intelligent Automation and Soft Computing</a> </i> &nbsp;
Using Convolution Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) deep learning applications, a multi-model fruit image identification system was created.  ...  Contemporary vision and pattern recognition issues such as image, face, fingerprint identification, and recognition, DNA sequencing, often have a large number of properties and classes.  ...  Funding Statement: This research is funded by Taif University, TURSP-2020/150.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.32604/iasc.2022.022589">doi:10.32604/iasc.2022.022589</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/46fbo7huq5esreimtoer2y2afu">fatcat:46fbo7huq5esreimtoer2y2afu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220301154236/https://www.techscience.com/ueditor/files/iasc/TSP_IASC-33-1/TSP_IASC_22589/TSP_IASC_22589.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/f3/ca/f3ca7e56973c664689b93cc287f47d1a6ec32d03.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.32604/iasc.2022.022589"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

HRGE-Net: Hierarchical Relational Graph Embedding Network for Multi-view 3D Shape Recognition [article]

Xin Wei, Ruixuan Yu, Jian Sun
<span title="2019-08-27">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
View-based approach that recognizes 3D shape through its projected 2D images achieved state-of-the-art performance for 3D shape recognition.  ...  One essential challenge for view-based approach is how to aggregate the multi-view features extracted from 2D images to be a global 3D shape descriptor.  ...  Voxel-based methods represent a 3D shape by a collection of voxels [25] in 3D Euclidean space, then build neural networks on voxels to learn the 3D features for recognition [34, 20] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1908.10098v1">arXiv:1908.10098v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mvf4f7z7mzeltadlfjo2wdir6y">fatcat:mvf4f7z7mzeltadlfjo2wdir6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200826152858/https://arxiv.org/pdf/1908.10098v1.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/61/2b/612b4b3a0bb4b305b9b00561b0b19c27462c3fab.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1908.10098v1" 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>

Research on the Brain-inspired Cross-modal Neural Cognitive Computing Framework [article]

Yang Liu
<span title="2018-05-31">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Furthermore, the semantic-oriented hierarchical Cross-modal Neural Cognitive Computing (CNCC) framework was proposed based on MNCC model, and formal description and analysis for CNCC framework was given  ...  The Multimedia Neural Cognitive Computing (MNCC) model was designed based on the nervous mechanism and cognitive architecture.  ...  It extracts the semantic label from representation media by multiple steps such as region of interest extraction, saliency target detection, object-oriented incremental recognition, multi-scale target  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1805.01385v2">arXiv:1805.01385v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7zj5oejdxrelbmokc37zhxex5y">fatcat:7zj5oejdxrelbmokc37zhxex5y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200930060237/https://arxiv.org/ftp/arxiv/papers/1805/1805.01385.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/3e/57/3e572869ac985392742cb7f528cea0c3c85cf1d4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1805.01385v2" 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>

Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19 [article]

Ioannis D. Apostolopoulos, Mpesiana Tzani
<span title="2020-11-23">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
for defect detection and industrial object recognition.  ...  Although Deep Learning has been advancing, allowing for real-time object detection and other tasks, little has been investigated about the effectiveness of specially designed Convolutional Neural Networks  ...  Material and Methods Deep Learning with Multilevel Virtual Geometry Group 19 network (MVGG19) The main advantage of deep Learning with Convolutional Neural Networks lies in extracting new features from  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.11305v1">arXiv:2011.11305v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/a7yspv5irbavnk7iwftq7muqj4">fatcat:a7yspv5irbavnk7iwftq7muqj4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201127013016/https://arxiv.org/ftp/arxiv/papers/2011/2011.11305.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/11/59/1159f27348c4591e498023fabb933dda0ad609b0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.11305v1" 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>

Emergence of higher-level neuron properties using a hierarchical statistical distribution model

Ning Xian, YiMin Deng, HaiBin Duan
<span title="2019-03-06">2019</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qfrmlo42brf2bmjk4rt4r33sfa" style="color: black;">Science China Technological Sciences</a> </i> &nbsp;
Essential to visual tasks such as object recognition is the formation of effective representations that generalize from specific instances of visual input.  ...  Two layers of our hierarchical model are presented to extract spiking activities of excitatory neurons decorrelated by inhibitory neurons and to construct the statistical patterns of input data, respectively  ...  , object recognition [14] and pose estimation [15] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11431-018-9327-9">doi:10.1007/s11431-018-9327-9</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4gzlnz3ufzgv3khdojbh5qis4m">fatcat:4gzlnz3ufzgv3khdojbh5qis4m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190502152746/https://link.springer.com/content/pdf/10.1007%2Fs11431-018-9327-9.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/4a/d9/4ad9ca2cd8af74fba97fb021b9f77e1b8160a1d5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11431-018-9327-9"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Learning a Hierarchical Latent-Variable Model of 3D Shapes [article]

Shikun Liu, C. Lee Giles, Alexander G. Ororbia II
<span title="2018-08-04">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Through the use of skip-connections, our model can successfully learn and infer a latent, hierarchical representation of objects.  ...  We propose the Variational Shape Learner (VSL), a generative model that learns the underlying structure of voxelized 3D shapes in an unsupervised fashion.  ...  One study, amidst the rise of neural network-based approaches to 3D object recognition, that is most relevant to this paper is that of [45] , which presented promising results and a benchmark for 3D model  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1705.05994v4">arXiv:1705.05994v4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7xmf33hcangffbgjw5ssxuals4">fatcat:7xmf33hcangffbgjw5ssxuals4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200906044349/https://arxiv.org/pdf/1705.05994v4.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/df/58/df581869a48f1601ad875f215c21ffc465b76bf5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1705.05994v4" 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>

The analysis of plants image recognition based on deep learning and artificial neural network

Jiang Huixian
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Firstly, plant leaf images are segmented by various methods, and then feature extraction algorithm is used to extract leaf shape and texture features from leaf sample images.  ...  Deep learning is the abbreviation of deep neural network learning method and belongs to neural network structure.  ...  The contributions of the proposed work are as follows: Acknowledgment The authors would like to thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.2986946">doi:10.1109/access.2020.2986946</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/s2nfopfrybdehps7vyjgoklj54">fatcat:s2nfopfrybdehps7vyjgoklj54</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201107204053/https://ieeexplore.ieee.org/ielx7/6287639/8948470/09062591.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/f8/7df8049e19feb72ca3bdfbf367b440a3759b23a7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.2986946"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Predicting Object Dynamics from Visual Images through Active Sensing Experiences

Shun Nishide, Tetsuya Ogata, Jun Tani, Kazunori Komatani, Hiroshi G. Okuno
<span title="">2007</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rytolcxr5rgw3dx2hhx2tlpo6q" style="color: black;">Engineering of Complex Computer Systems (ICECCS), Proceedings of the IEEE International Conference on</a> </i> &nbsp;
The acquired PB values, static images of objects and robot motor values are input into a hierarchical neural network to link the images to dynamic features (PB values).  ...  The neural network extracts prominent features that each induce object dynamics.  ...  Acknowledgements This research was partially supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Young Scientists (A) (No. 17680017, 2005-2007) , and Kayamori Foundation  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/robot.2007.363841">doi:10.1109/robot.2007.363841</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icra/NishideOTKO07.html">dblp:conf/icra/NishideOTKO07</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nrwex4a4yvdu5izebtmh3c5aha">fatcat:nrwex4a4yvdu5izebtmh3c5aha</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20090115235748/http://www.bdc.brain.riken.go.jp/~tani/papers/AR_nishide.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/b4/c0/b4c0d66508f299407cdb26c7c37eee848ee1e919.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/robot.2007.363841"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

From data topology to a modular classifier

Abdellatif Ennaji, Arnaud Ribert, Yves Lecourtier
<span title="2003-08-01">2003</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qlbwpi6y5ratlbyijgcz2zwany" style="color: black;">International Journal on Document Analysis and Recognition</a> </i> &nbsp;
The obtained global classifier is comprised of a set of cooperating neural networks and completed by a K-nearest neighbor classifier charged with treating elements rejected by all the neural networks.  ...  Experimental results for the handwritten digit recognition problem and comparison with neural and statistical nonmodular classifiers are given.  ...  In light of the above, the proposed approach tends to reach this objective by splitting the initial classification task into a simpler sub-tasks obtained by extracting the topology of the learning data  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10032-002-0095-3">doi:10.1007/s10032-002-0095-3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ipq45qmnhzbi5cb764tppce4nu">fatcat:ipq45qmnhzbi5cb764tppce4nu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170927090920/https://hal.archives-ouvertes.fr/hal-00280681/document" 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/e1/c1e11ae50f4d5108c0cd708dd61e4cab9bae0df7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10032-002-0095-3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>
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