A survey on wearable sensor modality centred human activity recognition in health care
Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …
population structure. Aging-caused changes, such as physical or cognitive decline, could …
Deep learning: a rapid and efficient route to automatic metasurface design
T Qiu, X Shi, J Wang, Y Li, S Qu, Q Cheng… - Advanced …, 2019 - Wiley Online Library
Metasurfaces provide unprecedented routes to manipulations on electromagnetic waves,
which can realize many exotic functionalities. Despite the rapid development of …
which can realize many exotic functionalities. Despite the rapid development of …
Learning adaptive discriminative correlation filters via temporal consistency preserving spatial feature selection for robust visual object tracking
With efficient appearance learning models, discriminative correlation filter (DCF) has been
proven to be very successful in recent video object tracking benchmarks and competitions …
proven to be very successful in recent video object tracking benchmarks and competitions …
Joint group feature selection and discriminative filter learning for robust visual object tracking
We propose a new Group Feature Selection method for Discriminative Correlation Filters
(GFS-DCF) based visual object tracking. The key innovation of the proposed method is to …
(GFS-DCF) based visual object tracking. The key innovation of the proposed method is to …
Feature selection for neural networks using group lasso regularization
We propose an embedded/integrated feature selection method based on neural networks
with Group Lasso penalty. Group Lasso regularization is considered to produce sparsity on …
with Group Lasso penalty. Group Lasso regularization is considered to produce sparsity on …
Transformed ℓ1 regularization for learning sparse deep neural networks
R Ma, J Miao, L Niu, P Zhang - Neural Networks, 2019 - Elsevier
Abstract Deep Neural Networks (DNNs) have achieved extraordinary success in numerous
areas. However, DNNs often carry a large number of weight parameters, leading to the …
areas. However, DNNs often carry a large number of weight parameters, leading to the …
Discriminative low-rank preserving projection for dimensionality reduction
Z Liu, J Wang, G Liu, L Zhang - Applied soft computing, 2019 - Elsevier
As an effective image clustering tool, low-rank representation (LRR) can capture the intrinsic
representation of the observed samples. However, firstly, the good representation does not …
representation of the observed samples. However, firstly, the good representation does not …
Learning latent low-rank and sparse embedding for robust image feature extraction
Z Ren, Q Sun, B Wu, X Zhang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
To defy the curse of dimensionality, the inputs are always projected from the original high-
dimensional space into the target low-dimension space for feature extraction. However, due …
dimensional space into the target low-dimension space for feature extraction. However, due …
Robust clinical marker identification for diabetic kidney disease with ensemble feature selection
Objective Diabetic kidney disease (DKD) is one of the most frequent complications in
diabetes associated with substantial morbidity and mortality. To accelerate DKD risk factor …
diabetes associated with substantial morbidity and mortality. To accelerate DKD risk factor …
AFS: An attention-based mechanism for supervised feature selection
N Gui, D Ge, Z Hu - Proceedings of the AAAI conference on artificial …, 2019 - aaai.org
As an effective data preprocessing step, feature selection has shown its effectiveness to
prepare high-dimensional data for many machine learning tasks. The proliferation of high di …
prepare high-dimensional data for many machine learning tasks. The proliferation of high di …