Multimodal Sparse Representation Learning and Applications
نویسندگان
چکیده
منابع مشابه
Multimodal sparse representation learning and applications
Unsupervised methods have proven effective for discriminative tasks in a singlemodality scenario. In this paper, we present a multimodal framework for learning sparse representations that can capture semantic correlation between modalities. The framework can model relationships at a higher level by forcing the shared sparse representation. In particular, we propose the use of joint dictionary l...
متن کاملJoint Sparse Representation for Robust Multimodal
Joint Sparse Representation for Robust Multimodal Biometrics Recognition Report Title Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attent...
متن کاملDictionary Learning for Scalable Sparse Image Representation with Applications
This paper introduces a novel design for the dictionary learning algorithm, intended for scalable sparse representation of high motion video sequences and natural images. The proposed algorithm is built upon the foundation of the K-SVD framework originally designed to learn non-scalable dictionaries for natural images. Proposed design is mainly motivated by the main perception characteristic of...
متن کاملDeblocking Joint Photographic Experts Group Compressed Images via Self-learning Sparse Representation
JPEG is one of the most widely used image compression method, but it causes annoying blocking artifacts at low bit-rates. Sparse representation is an efficient technique which can solve many inverse problems in image processing applications such as denoising and deblocking. In this paper, a post-processing method is proposed for reducing JPEG blocking effects via sparse representation. In this ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of AI Humanities
سال: 2018
ISSN: 2635-4691
DOI: 10.46397/jaih.2.2