ARTÍCULO
TITULO

Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations

Kim    
Tae-Kyun    
Kittler    
Josef    
Cipolla    
Roberto    

Resumen

No disponible

 Artículos similares

       
 
Elena Martínez-Fernandez, Ignacio Rojas-Valenzuela, Olga Valenzuela and Ignacio Rojas    
The diagnosis of different pathologies and stages of cancer using whole histopathology slide images (WSI) is the gold standard for determining the degree of tissue metastasis. The use of deep learning systems in the field of medical images, especially hi... ver más
Revista: Applied Sciences

 
Ning Wang, Zhong Ma, Pengcheng Huo, Xi Liu, Zhao He and Kedi Lu    
Crop yield prediction is essential for tasks like determining the optimal profile of crops to be planted, allocating government resources, effectively planning and preparing for aid distribution, making decisions about imports, and so on. Crop yield pred... ver más
Revista: Applied Sciences

 
Li-Na Wang, Guoqiang Zhong, Yaxin Shi and Mohamed Cheriet    
Most of the dimensionality reduction algorithms assume that data are independent and identically distributed (i.i.d.). In real-world applications, however, sometimes there exist relationships between data. Some relational learning methods have been propo... ver más
Revista: Algorithms

 
Shumin Lai, Longjun Huang, Ping Li, Zhenzhen Luo, Jianzhong Wang and Yugen Yi    
In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve the p... ver más
Revista: Algorithms

 
Mei Bie, Huan Xu, Quanle Liu, Yan Gao, Kai Song and Xiangjiu Che    
Facial expression recognition (FER) is an important field in computer vision with many practical applications. However, one of the challenges in FER is dealing with small sample data, where the number of samples available for training machine learning al... ver más
Revista: Applied Sciences