A survey on deep learning for human activity recognition
Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …
home. In this study, we provide a comprehensive survey on recent advances and challenges …
[HTML][HTML] Deep learning classifiers for hyperspectral imaging: A review
Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
Single-cell multiregion dissection of Alzheimer's disease
Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways
that underlie its pathological progression across brain regions remain poorly understood …
that underlie its pathological progression across brain regions remain poorly understood …
Normalization techniques in training dnns: Methodology, analysis and application
Normalization techniques are essential for accelerating the training and improving the
generalization of deep neural networks (DNNs), and have successfully been used in various …
generalization of deep neural networks (DNNs), and have successfully been used in various …
Ranpac: Random projections and pre-trained models for continual learning
Continual learning (CL) aims to incrementally learn different tasks (such as classification) in
a non-stationary data stream without forgetting old ones. Most CL works focus on tackling …
a non-stationary data stream without forgetting old ones. Most CL works focus on tackling …
Camp: Camera preconditioning for neural radiance fields
Neural Radiance Fields (NeRF) can be optimized to obtain high-fidelity 3D scene
reconstructions of objects and large-scale scenes. However, NeRFs require accurate …
reconstructions of objects and large-scale scenes. However, NeRFs require accurate …
Solving the spike sorting problem with Kilosort
Spike sorting is the computational process of extracting the firing times of single neurons
from recordings of local electrical fields. This is an important but hard problem in …
from recordings of local electrical fields. This is an important but hard problem in …
Spike sorting with Kilosort4
Spike sorting is the computational process of extracting the firing times of single neurons
from recordings of local electrical fields. This is an important but hard problem in …
from recordings of local electrical fields. This is an important but hard problem in …
Avatar-net: Multi-scale zero-shot style transfer by feature decoration
Zero-shot artistic style transfer is an important image synthesis problem aiming at
transferring arbitrary style into content images. However, the trade-off between the …
transferring arbitrary style into content images. However, the trade-off between the …
Benchmark of filter methods for feature selection in high-dimensional gene expression survival data
A Bommert, T Welchowski, M Schmid… - Briefings in …, 2022 - academic.oup.com
Feature selection is crucial for the analysis of high-dimensional data, but benchmark studies
for data with a survival outcome are rare. We compare 14 filter methods for feature selection …
for data with a survival outcome are rare. We compare 14 filter methods for feature selection …