State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
Classical and modern face recognition approaches: a complete review
Human face recognition have been an active research area for the last few decades.
Especially, during the last five years, it has gained significant research attention from …
Especially, during the last five years, it has gained significant research attention from …
Removing rain from a single image via discriminative sparse coding
Visual distortions on images caused by bad weather conditions can have a negative impact
on the performance of many outdoor vision systems. One often seen bad weather is rain …
on the performance of many outdoor vision systems. One often seen bad weather is rain …
A survey of sparse representation: algorithms and applications
Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …
processing, image processing, computer vision, and pattern recognition. Sparse …
Label consistent K-SVD: Learning a discriminative dictionary for recognition
A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse
coding is presented. In addition to using class labels of training data, we also associate label …
coding is presented. In addition to using class labels of training data, we also associate label …
Deep convolutional dictionary learning for image denoising
Inspired by the great success of deep neural networks (DNNs), many unfolding methods
have been proposed to integrate traditional image modeling techniques, such as dictionary …
have been proposed to integrate traditional image modeling techniques, such as dictionary …
A survey of deep learning methods and software tools for image classification and object detection
PN Druzhkov, VD Kustikova - Pattern Recognition and Image Analysis, 2016 - Springer
Deep learning methods for image classification and object detection are overviewed. In
particular we consider such deep models as autoencoders, restricted Boltzmann machines …
particular we consider such deep models as autoencoders, restricted Boltzmann machines …
Sparse representation based fisher discrimination dictionary learning for image classification
The employed dictionary plays an important role in sparse representation or sparse coding
based image reconstruction and classification, while learning dictionaries from the training …
based image reconstruction and classification, while learning dictionaries from the training …
Fisher discrimination dictionary learning for sparse representation
Sparse representation based classification has led to interesting image recognition results,
while the dictionary used for sparse coding plays a key role in it. This paper presents a novel …
while the dictionary used for sparse coding plays a key role in it. This paper presents a novel …