Artigos de revistas sobre o tema "Sparse features"
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Caragea, Cornelia, Adrian Silvescu e Prasenjit Mitra. "Combining Hashing and Abstraction in Sparse High Dimensional Feature Spaces". Proceedings of the AAAI Conference on Artificial Intelligence 26, n.º 1 (20 de setembro de 2021): 3–9. http://dx.doi.org/10.1609/aaai.v26i1.8117.
Texto completo da fonteSimion, Georgiana. "Sparse Features for Finger Detection". Advanced Engineering Forum 8-9 (junho de 2013): 535–42. http://dx.doi.org/10.4028/www.scientific.net/aef.8-9.535.
Texto completo da fonteKronvall, Ted, Maria Juhlin, Johan Swärd, Stefan I. Adalbjörnsson e Andreas Jakobsson. "Sparse modeling of chroma features". Signal Processing 130 (janeiro de 2017): 105–17. http://dx.doi.org/10.1016/j.sigpro.2016.06.020.
Texto completo da fonteHe, Wangpeng, Peipei Zhang, Xuan Liu, Binqiang Chen e Baolong Guo. "Group-Sparse Feature Extraction via Ensemble Generalized Minimax-Concave Penalty for Wind-Turbine-Fault Diagnosis". Sustainability 14, n.º 24 (14 de dezembro de 2022): 16793. http://dx.doi.org/10.3390/su142416793.
Texto completo da fonteBanihashem, Kiarash, Mohammad Hajiaghayi e Max Springer. "Optimal Sparse Recovery with Decision Stumps". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 6 (26 de junho de 2023): 6745–52. http://dx.doi.org/10.1609/aaai.v37i6.25827.
Texto completo da fonteXing, Zhan, Jianhui Lin, Yan Huang e Cai Yi. "A Feature Extraction Method of Wheelset-Bearing Fault Based on Wavelet Sparse Representation with Adaptive Local Iterative Filtering". Shock and Vibration 2020 (25 de julho de 2020): 1–20. http://dx.doi.org/10.1155/2020/2019821.
Texto completo da fonteWei, Wang, Tang Can, Wang Xin, Luo Yanhong, Hu Yongle e Li Ji. "Image Object Recognition via Deep Feature-Based Adaptive Joint Sparse Representation". Computational Intelligence and Neuroscience 2019 (21 de novembro de 2019): 1–9. http://dx.doi.org/10.1155/2019/8258275.
Texto completo da fonteYANG, B. J. "DOMINANT EIGENVECTOR AND EIGENVALUE ALGORITHM IN SPARSE NETWORK SPECTRAL CLUSTERING". Latin American Applied Research - An international journal 48, n.º 4 (31 de outubro de 2018): 323–28. http://dx.doi.org/10.52292/j.laar.2018.248.
Texto completo da fonteSUN, JUN, WENYUAN WANG, QING ZHUO e CHENGYUAN MA. "DISCRIMINATORY SPARSE CODING AND ITS APPLICATION TO FACE RECOGNITION". International Journal of Image and Graphics 03, n.º 03 (julho de 2003): 503–21. http://dx.doi.org/10.1142/s0219467803001135.
Texto completo da fonteGrimes, David B., e Rajesh P. N. Rao. "Bilinear Sparse Coding for Invariant Vision". Neural Computation 17, n.º 1 (1 de janeiro de 2005): 47–73. http://dx.doi.org/10.1162/0899766052530893.
Texto completo da fonteAnwar, Shahzad, Qingjie Zhao, Muhammad Farhan Manzoor e Saqib Ishaq Khan. "Saliency Detection Using Sparse and Nonlinear Feature Representation". Scientific World Journal 2014 (2014): 1–16. http://dx.doi.org/10.1155/2014/137349.
Texto completo da fonteFeng, Shang, Haifeng Li, Lin Ma e Zhongliang Xu. "An EEG Feature Extraction Method Based on Sparse Dictionary Self-Organizing Map for Event-Related Potential Recognition". Algorithms 13, n.º 10 (13 de outubro de 2020): 259. http://dx.doi.org/10.3390/a13100259.
Texto completo da fonteSun, Zhenzhen, e Yuanlong Yu. "Fast Approximation for Sparse Coding with Applications to Object Recognition". Sensors 21, n.º 4 (19 de fevereiro de 2021): 1442. http://dx.doi.org/10.3390/s21041442.
Texto completo da fonteLi, Jiaye, Guoqiu Wen, Jiangzhang Gan, Leyuan Zhang e Shanwen Zhang. "Sparse Nonlinear Feature Selection Algorithm via Local Structure Learning". Emerging Science Journal 3, n.º 2 (9 de abril de 2019): 115. http://dx.doi.org/10.28991/esj-2019-01175.
Texto completo da fonteWang, Xin, Can Tang, Ji Li, Peng Zhang e Wei Wang. "Image Target Recognition via Mixed Feature-Based Joint Sparse Representation". Computational Intelligence and Neuroscience 2020 (10 de agosto de 2020): 1–8. http://dx.doi.org/10.1155/2020/8887453.
Texto completo da fonteShen, Ning-Min, Jing Li, Pei-Yun Zhou, Ying Huo e Yi Zhuang. "BSFCoS: Block and Sparse Principal Component Analysis-Based Fast Co-Saliency Detection Method". International Journal of Pattern Recognition and Artificial Intelligence 30, n.º 01 (30 de dezembro de 2015): 1655003. http://dx.doi.org/10.1142/s021800141655003x.
Texto completo da fonteLi, Ning, Weiping Tu e Haojun Ai. "A Sparse Feature Matching Model Using a Transformer towards Large-View Indoor Visual Localization". Wireless Communications and Mobile Computing 2022 (4 de julho de 2022): 1–12. http://dx.doi.org/10.1155/2022/1243041.
Texto completo da fonteZang, Mujun, Dunwei Wen, Tong Liu, Hailin Zou e Chanjuan Liu. "A Fast Sparse Coding Method for Image Classification". Applied Sciences 9, n.º 3 (1 de fevereiro de 2019): 505. http://dx.doi.org/10.3390/app9030505.
Texto completo da fonteZhao, Yue, e Jianbo Su. "New Sparse Facial Feature Description Model Based on Salience Evaluation of Regions and Features". International Journal of Pattern Recognition and Artificial Intelligence 29, n.º 05 (9 de julho de 2015): 1556007. http://dx.doi.org/10.1142/s0218001415560078.
Texto completo da fonteZhou, Junxiu, Yangyang Tao e Xian Liu. "Tensor Decomposition for Salient Object Detection in Images". Big Data and Cognitive Computing 3, n.º 2 (19 de junho de 2019): 33. http://dx.doi.org/10.3390/bdcc3020033.
Texto completo da fonteHarris, Chelsea, Uchenna Okorie e Sokratis Makrogiannis. "Spatially localized sparse approximations of deep features for breast mass characterization". Mathematical Biosciences and Engineering 20, n.º 9 (2023): 15859–82. http://dx.doi.org/10.3934/mbe.2023706.
Texto completo da fonteLiang, Lin, Xingyun Ding, Fei Liu, Yuanming Chen e Haobin Wen. "Feature Extraction Using Sparse Kernel Non-Negative Matrix Factorization for Rolling Element Bearing Diagnosis". Sensors 21, n.º 11 (25 de maio de 2021): 3680. http://dx.doi.org/10.3390/s21113680.
Texto completo da fonteWang, Longhao, Chaozhen Lan, Beibei Wu, Tian Gao, Zijun Wei e Fushan Yao. "A Method for Detecting Feature-Sparse Regions and Matching Enhancement". Remote Sensing 14, n.º 24 (8 de dezembro de 2022): 6214. http://dx.doi.org/10.3390/rs14246214.
Texto completo da fonteNan Dong, Fuqiang Liu e Zhipeng Li. "Crowd Density Estimation Using Sparse Texture Features". Journal of Convergence Information Technology 5, n.º 6 (31 de agosto de 2010): 125–37. http://dx.doi.org/10.4156/jcit.vol5.issue6.13.
Texto completo da fonteLi, B., Q. Meng e H. Holstein. "Articulated Pose Identification With Sparse Point Features". IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 34, n.º 3 (junho de 2004): 1412–22. http://dx.doi.org/10.1109/tsmcb.2004.825914.
Texto completo da fonteHan, H., e X. J. Li. "Human action recognition with sparse geometric features". Imaging Science Journal 63, n.º 1 (14 de outubro de 2014): 45–53. http://dx.doi.org/10.1179/1743131x14y.0000000091.
Texto completo da fonteZhou, Hongdi, Lin Zhu e Xixing Li. "Fault Diagnosis Method for Rolling Bearing Based on Sparse Principal Subspace Discriminant Analysis". Shock and Vibration 2022 (13 de abril de 2022): 1–12. http://dx.doi.org/10.1155/2022/8946094.
Texto completo da fonteWersing, Heiko, e Edgar Körner. "Learning Optimized Features for Hierarchical Models of Invariant Object Recognition". Neural Computation 15, n.º 7 (1 de julho de 2003): 1559–88. http://dx.doi.org/10.1162/089976603321891800.
Texto completo da fonteWang, HongChao, e WenLiao Du. "Intelligent diagnosis of rolling bearing compound faults based on device state dictionary set sparse decomposition feature extraction–hidden Markov model". Advances in Mechanical Engineering 12, n.º 6 (junho de 2020): 168781402093046. http://dx.doi.org/10.1177/1687814020930469.
Texto completo da fonteNardone, Davide, Angelo Ciaramella e Antonino Staiano. "A Sparse-Modeling Based Approach for Class Specific Feature Selection". PeerJ Computer Science 5 (18 de novembro de 2019): e237. http://dx.doi.org/10.7717/peerj-cs.237.
Texto completo da fontePeng, Wei, Dong Wang, Changqing Shen e Dongni Liu. "Sparse Signal Representations of Bearing Fault Signals for Exhibiting Bearing Fault Features". Shock and Vibration 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/1835127.
Texto completo da fonteZhang, Zongzhen, Shunming Li, Zenghui An e Yu Xin. "Fast convolution sparse filtering and its application on gearbox fault diagnosis". Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, n.º 9 (6 de abril de 2020): 2291–304. http://dx.doi.org/10.1177/0954407020907818.
Texto completo da fonteXia, Shiqi, Yimin Xia e Jiawei Xiang. "Piston Wear Detection and Feature Selection Based on Vibration Signals Using the Improved Spare Support Vector Machine for Axial Piston Pumps". Materials 15, n.º 23 (29 de novembro de 2022): 8504. http://dx.doi.org/10.3390/ma15238504.
Texto completo da fonteAfshar, Majid, e Hamid Usefi. "Optimizing feature selection methods by removing irrelevant features using sparse least squares". Expert Systems with Applications 200 (agosto de 2022): 116928. http://dx.doi.org/10.1016/j.eswa.2022.116928.
Texto completo da fonteDai, Ling, Guangyun Zhang, Jinqi Gong e Rongting Zhang. "Autonomous Learning Interactive Features for Hyperspectral Remotely Sensed Data". Applied Sciences 11, n.º 21 (8 de novembro de 2021): 10502. http://dx.doi.org/10.3390/app112110502.
Texto completo da fonteYan, Jingjie, Xiaolan Wang, Weiyi Gu e LiLi Ma. "Speech Emotion Recognition Based on Sparse Representation". Archives of Acoustics 38, n.º 4 (1 de dezembro de 2013): 465–70. http://dx.doi.org/10.2478/aoa-2013-0055.
Texto completo da fonteHenry, Rawn, Olivia Hsu, Rohan Yadav, Stephen Chou, Kunle Olukotun, Saman Amarasinghe e Fredrik Kjolstad. "Compilation of sparse array programming models". Proceedings of the ACM on Programming Languages 5, OOPSLA (20 de outubro de 2021): 1–29. http://dx.doi.org/10.1145/3485505.
Texto completo da fonteGuo, Xiyang. "Research on Mushroom Image Classification Algorithm Based on Deep Sparse Dictionary Learning". Academic Journal of Science and Technology 9, n.º 1 (20 de janeiro de 2024): 235–40. http://dx.doi.org/10.54097/1f3xnx82.
Texto completo da fonteHe, Jiahui, Zhijun Cheng e Bo Guo. "Anomaly Detection in Satellite Telemetry Data Using a Sparse Feature-Based Method". Sensors 22, n.º 17 (24 de agosto de 2022): 6358. http://dx.doi.org/10.3390/s22176358.
Texto completo da fonteXidao, Luan, Xie Yuxiang, Zhang Lili, Zhang Xin, Li Chen e He Jingmeng. "An Image Similarity Acceleration Detection Algorithm Based on Sparse Coding". Mathematical Problems in Engineering 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/1917421.
Texto completo da fonteChen, Zhong, Shengwu Xiong, Zhixiang Fang, Ruiling Zhang, Xiangzhen Kong e Yi Rong. "Topologically Ordered Feature Extraction Based on Sparse Group Restricted Boltzmann Machines". Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/267478.
Texto completo da fonteZhang, Yayu, Yuhua Qian, Guoshuai Ma, Keyin Zheng, Guoqing Liu e Qingfu Zhang. "Learning Multi-Task Sparse Representation Based on Fisher Information". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 15 (24 de março de 2024): 16899–907. http://dx.doi.org/10.1609/aaai.v38i15.29632.
Texto completo da fonteWang, Bin, Yu Liu, Wei Wang, Wei Xu e Mao Jun Zhang. "Local Spatiotemporal Coding and Sparse Representation Based Human Action Recognition". Applied Mechanics and Materials 401-403 (setembro de 2013): 1555–60. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.1555.
Texto completo da fonteKim, Hyuncheol, e Joonki Paik. "Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity". Abstract and Applied Analysis 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/147353.
Texto completo da fonteJin, Ju Bo, e Yu Xi Liu. "Sparse Representation of the Human Vision Information and the Saliency Detection Algorithm". Applied Mechanics and Materials 513-517 (fevereiro de 2014): 3349–53. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3349.
Texto completo da fonteWang, Qing Wei, Zi Lu Ying e Lian Wen Huang. "Face Recognition Algorithm Based on Haar-Like Features and Gentle Adaboost Feature Selection via Sparse Representation". Applied Mechanics and Materials 742 (março de 2015): 299–302. http://dx.doi.org/10.4028/www.scientific.net/amm.742.299.
Texto completo da fonteWang, Yong. "Online electronic signature recognition using sparse classification techniques that support neural models". Journal of Computational Methods in Sciences and Engineering 24, n.º 1 (14 de março de 2024): 263–75. http://dx.doi.org/10.3233/jcm-237025.
Texto completo da fonteYang, Honghui, e Shuzhen Yi. "Underwater Acoustic Target Feature Fusion Method Based on Multi-Kernel Sparsity Preserve Multi-Set Canonical Correlation Analysis". Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 37, n.º 1 (fevereiro de 2019): 87–92. http://dx.doi.org/10.1051/jnwpu/20193710087.
Texto completo da fonteYuan, Ye, Jiang Chen, Hong Lang e Jian (John) Lu. "Exploring the Efficacy of Sparse Feature in Pavement Distress Image Classification: A Focus on Pavement-Specific Knowledge". Applied Sciences 13, n.º 18 (5 de setembro de 2023): 9996. http://dx.doi.org/10.3390/app13189996.
Texto completo da fonteHasler, Stephan, Heiko Wersing e Edgar Körner. "Combining Reconstruction and Discrimination with Class-Specific Sparse Coding". Neural Computation 19, n.º 7 (julho de 2007): 1897–918. http://dx.doi.org/10.1162/neco.2007.19.7.1897.
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