Ensemble unsupervised autoencoders and Gaussian mixture model for cyberattack detection
P An, Z Wang, C Zhang - Information Processing & Management, 2022 - Elsevier
Previous studies have adopted unsupervised machine learning with dimension reduction
functions for cyberattack detection, which are limited to performing robust anomaly detection …
functions for cyberattack detection, which are limited to performing robust anomaly detection …
V2v-posenet: Voxel-to-voxel prediction network for accurate 3d hand and human pose estimation from a single depth map
Most of the existing deep learning-based methods for 3D hand and human pose estimation
from a single depth map are based on a common framework that takes a 2D depth map and …
from a single depth map are based on a common framework that takes a 2D depth map and …
Deepprior++: Improving fast and accurate 3d hand pose estimation
M Oberweger, V Lepetit - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
DeepPrior is a simple approach based on Deep Learning that predicts the joint 3D locations
of a hand given a depth map. Since its publication early 2015, it has been outperformed by …
of a hand given a depth map. Since its publication early 2015, it has been outperformed by …
A2j: Anchor-to-joint regression network for 3d articulated pose estimation from a single depth image
For 3D hand and body pose estimation task in depth image, a novel anchor-based approach
termed Anchor-to-Joint regression network (A2J) with the end-to-end learning ability is …
termed Anchor-to-Joint regression network (A2J) with the end-to-end learning ability is …
Pose guided structured region ensemble network for cascaded hand pose estimation
Hand pose estimation from single depth images is an essential topic in computer vision and
human computer interaction. Despite recent advancements in this area promoted by …
human computer interaction. Despite recent advancements in this area promoted by …
Federated multidomain learning with graph ensemble autoencoder GMM for emotion recognition
Facial expression cognition technology continues to face challenges from certain
perspectives despite the fact that there have been significant recent learning advances in …
perspectives despite the fact that there have been significant recent learning advances in …
A survey on 3D hand pose estimation: Cameras, methods, and datasets
R Li, Z Liu, J Tan - Pattern Recognition, 2019 - Elsevier
Abstract 3D Hand pose estimation has received an increasing amount of attention,
especially since consumer depth cameras came onto the market in 2010. Although …
especially since consumer depth cameras came onto the market in 2010. Although …
Shpr-net: Deep semantic hand pose regression from point clouds
3-D hand pose estimation is an essential problem for human-computer interaction. Most of
the existing depth-based hand pose estimation methods consume 2-D depth map or 3-D …
the existing depth-based hand pose estimation methods consume 2-D depth map or 3-D …
Multi-resolution attention convolutional neural network for crowd counting
Estimating crowd counts remains a challenging task due to the problems of scale variations,
non-uniform distribution and complex backgrounds. In this paper, we propose a multi …
non-uniform distribution and complex backgrounds. In this paper, we propose a multi …
Gan-based virtual-to-real image translation for urban scene semantic segmentation
Semantic image segmentation requires large amounts of pixel-wise labeled training data.
Creating such data generally requires labor-intensive human manual annotation. Thus …
Creating such data generally requires labor-intensive human manual annotation. Thus …