Gotowa bibliografia na temat „Hierarchical Pooling”
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Artykuły w czasopismach na temat "Hierarchical Pooling"
Fernando, Basura, i Stephen Gould. "Discriminatively Learned Hierarchical Rank Pooling Networks". International Journal of Computer Vision 124, nr 3 (24.06.2017): 335–55. http://dx.doi.org/10.1007/s11263-017-1030-x.
Pełny tekst źródłaRanjan, Ekagra, Soumya Sanyal i Partha Talukdar. "ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 04 (3.04.2020): 5470–77. http://dx.doi.org/10.1609/aaai.v34i04.5997.
Pełny tekst źródłaChen, Jiawang, i Zhenqiang Wu. "Learning Embedding for Signed Network in Social Media with Hierarchical Graph Pooling". Applied Sciences 12, nr 19 (28.09.2022): 9795. http://dx.doi.org/10.3390/app12199795.
Pełny tekst źródłaGrumitt, R. D. P., Luke R. P. Jew i C. Dickinson. "Hierarchical Bayesian CMB component separation with the No-U-Turn Sampler". Monthly Notices of the Royal Astronomical Society 496, nr 4 (26.06.2020): 4383–401. http://dx.doi.org/10.1093/mnras/staa1857.
Pełny tekst źródłaDevineni, Naresh, Upmanu Lall, Neil Pederson i Edward Cook. "A Tree-Ring-Based Reconstruction of Delaware River Basin Streamflow Using Hierarchical Bayesian Regression". Journal of Climate 26, nr 12 (15.06.2013): 4357–74. http://dx.doi.org/10.1175/jcli-d-11-00675.1.
Pełny tekst źródłaChen, Junying, i Ying Chen. "Saliency Enhanced Hierarchical Bilinear Pooling for Fine-Grained Classification". Journal of Computer-Aided Design & Computer Graphics 33, nr 2 (1.02.2021): 241–49. http://dx.doi.org/10.3724/sp.j.1089.2021.18399.
Pełny tekst źródłaSanchez-Giraldo, Luis G., Md Nasir Uddin Laskar i Odelia Schwartz. "Normalization and pooling in hierarchical models of natural images". Current Opinion in Neurobiology 55 (kwiecień 2019): 65–72. http://dx.doi.org/10.1016/j.conb.2019.01.008.
Pełny tekst źródłaTan, Min, Fu Yuan, Jun Yu, Guijun Wang i Xiaoling Gu. "Fine-grained Image Classification via Multi-scale Selective Hierarchical Biquadratic Pooling". ACM Transactions on Multimedia Computing, Communications, and Applications 18, nr 1s (28.02.2022): 1–23. http://dx.doi.org/10.1145/3492221.
Pełny tekst źródłaKo, Sung Moon, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee i Honglak Lee. "Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 7 (26.06.2023): 8334–42. http://dx.doi.org/10.1609/aaai.v37i7.26005.
Pełny tekst źródłaLi, Keqin. "Hierarchical Pooling Strategy Optimization for Accelerating Asymptomatic COVID-19 Screening". IEEE Open Journal of the Computer Society 1 (2020): 276–84. http://dx.doi.org/10.1109/ojcs.2020.3036581.
Pełny tekst źródłaRozprawy doktorskie na temat "Hierarchical Pooling"
Mazari, Ahmed. "Apprentissage profond pour la reconnaissance d’actions en vidéos". Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS171.
Pełny tekst źródłaNowadays, video contents are ubiquitous through the popular use of internet and smartphones, as well as social media. Many daily life applications such as video surveillance and video captioning, as well as scene understanding require sophisticated technologies to process video data. It becomes of crucial importance to develop automatic means to analyze and to interpret the large amount of available video data. In this thesis, we are interested in video action recognition, i.e. the problem of assigning action categories to sequences of videos. This can be seen as a key ingredient to build the next generation of vision systems. It is tackled with AI frameworks, mainly with ML and Deep ConvNets. Current ConvNets are increasingly deeper, data-hungrier and this makes their success tributary of the abundance of labeled training data. ConvNets also rely on (max or average) pooling which reduces dimensionality of output layers (and hence attenuates their sensitivity to the availability of labeled data); however, this process may dilute the information of upstream convolutional layers and thereby affect the discrimination power of the trained video representations, especially when the learned action categories are fine-grained
Części książek na temat "Hierarchical Pooling"
Zhang, Can, Yuexian Zou i Guang Chen. "Hierarchical Temporal Pooling for Efficient Online Action Recognition". W MultiMedia Modeling, 471–82. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05710-7_39.
Pełny tekst źródłaYu, Chaojian, Xinyi Zhao, Qi Zheng, Peng Zhang i Xinge You. "Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition". W Computer Vision – ECCV 2018, 595–610. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01270-0_35.
Pełny tekst źródłaLiu, Yan, Zhi Liu i Zhirong Lei. "Hierarchical Pooling Based Extreme Learning Machine for Image Classification". W Lecture Notes in Electrical Engineering, 1–9. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9698-5_1.
Pełny tekst źródłaThornton, John, Jolon Faichney, Michael Blumenstein i Trevor Hine. "Character Recognition Using Hierarchical Vector Quantization and Temporal Pooling". W AI 2008: Advances in Artificial Intelligence, 562–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89378-3_57.
Pełny tekst źródłaFei, Xiaohan, Konstantine Tsotsos i Stefano Soatto. "A Simple Hierarchical Pooling Data Structure for Loop Closure". W Computer Vision – ECCV 2016, 321–37. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46487-9_20.
Pełny tekst źródłaLiu, Peishuo, Cangqi Zhou, Xiao Liu, Jing Zhang i Qianmu Li. "Multi-Granularity Contrastive Learning for Graph with Hierarchical Pooling". W Artificial Neural Networks and Machine Learning – ICANN 2023, 499–511. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44216-2_41.
Pełny tekst źródłaZhao, Haifeng, Xiaoping Wu, Dejun Bao i Shaojie Zhang. "Intracranial Hematoma Classification Based on the Pyramid Hierarchical Bilinear Pooling". W Pattern Recognition and Computer Vision, 606–17. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88010-1_51.
Pełny tekst źródłaLiu, Wenya, Zhi Yang, Haitao Gan, Zhongwei Huang, Ran Zhou i Ming Shi. "Hierarchical Pooling Graph Convolutional Neural Network for Alzheimer’s Disease Diagnosis". W PRICAI 2023: Trends in Artificial Intelligence, 426–37. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-7019-3_39.
Pełny tekst źródłaBandyopadhyay, Sambaran, Manasvi Aggarwal i M. Narasimha Murty. "A Deep Hybrid Pooling Architecture for Graph Classification with Hierarchical Attention". W Advances in Knowledge Discovery and Data Mining, 554–65. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75762-5_44.
Pełny tekst źródłaOtter, Thomas, i Tetyana Kosyakova. "Implications of Linear Versus Dummy Coding for Pooling of Information in Hierarchical Models". W Quantitative Marketing and Marketing Management, 171–90. Wiesbaden: Gabler Verlag, 2012. http://dx.doi.org/10.1007/978-3-8349-3722-3_8.
Pełny tekst źródłaStreszczenia konferencji na temat "Hierarchical Pooling"
Pan, Zizheng, Bohan Zhuang, Jing Liu, Haoyu He i Jianfei Cai. "Scalable Vision Transformers with Hierarchical Pooling". W 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. http://dx.doi.org/10.1109/iccv48922.2021.00043.
Pełny tekst źródłaFernando, Basura, Peter Anderson, Marcus Hutter i Stephen Gould. "Discriminative Hierarchical Rank Pooling for Activity Recognition". W 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.212.
Pełny tekst źródłaBi, Liande, Xin Sun, Fei Zhou i Junyu Dong. "Hierarchical Triplet Attention Pooling for Graph Classification". W 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai52525.2021.00100.
Pełny tekst źródłaAli, Waqar, Sebastiano Vascon, Thilo Stadelmann i Marcello Pelillo. "Quasi-CliquePool: Hierarchical Graph Pooling for Graph Classification". W SAC '23: 38th ACM/SIGAPP Symposium on Applied Computing. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3555776.3578600.
Pełny tekst źródłaRoy, Kashob Kumar, Amit Roy, A. K. M. Mahbubur Rahman, M. Ashraful Amin i Amin Ahsan Ali. "Structure-Aware Hierarchical Graph Pooling using Information Bottleneck". W 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9533778.
Pełny tekst źródłaSu, Zidong, Zehui Hu i Yangding Li. "Hierarchical Graph Representation Learning with Local Capsule Pooling". W MMAsia '21: ACM Multimedia Asia. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3469877.3495645.
Pełny tekst źródłaHe, Ke-Xin, Yu-Han Shen i Wei-Qiang Zhang. "Hierarchical Pooling Structure for Weakly Labeled Sound Event Detection". W Interspeech 2019. ISCA: ISCA, 2019. http://dx.doi.org/10.21437/interspeech.2019-2049.
Pełny tekst źródłaRachmadi, Reza Fuad, Keiichi Uchimura, Gou Koutaki i Kohichi Ogata. "Hierarchical Spatial Pyramid Pooling for Fine-Grained Vehicle Classification". W 2018 International Workshop on Big Data and Information Security (IWBIS). IEEE, 2018. http://dx.doi.org/10.1109/iwbis.2018.8471695.
Pełny tekst źródłaGao, Lijian, Ling Zhou, Qirong Mao i Ming Dong. "Adaptive Hierarchical Pooling for Weakly-supervised Sound Event Detection". W MM '22: The 30th ACM International Conference on Multimedia. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3503161.3548097.
Pełny tekst źródłaYu, Hualei, Yirong Yao, Jinliang Yuan i Chongjun Wang. "DIPool: Degree-Induced Pooling for Hierarchical Graph Representation Learning". W 2022 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom). IEEE, 2022. http://dx.doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom57177.2022.00035.
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