Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Humor: 3d human motion model for robust pose estimation
We introduce HuMoR: a 3D Human Motion Model for Robust Estimation of temporal pose
and shape. Though substantial progress has been made in estimating 3D human motion …
and shape. Though substantial progress has been made in estimating 3D human motion …
Msr-gcn: Multi-scale residual graph convolution networks for human motion prediction
Human motion prediction is a challenging task due to the stochasticity and aperiodicity of
future poses. Recently, graph convolutional network has been proven to be very effective to …
future poses. Recently, graph convolutional network has been proven to be very effective to …
Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study
In this paper, we present a survey of deep learning approaches for cyber security intrusion
detection, the datasets used, and a comparative study. Specifically, we provide a review of …
detection, the datasets used, and a comparative study. Specifically, we provide a review of …
Space-time-separable graph convolutional network for pose forecasting
Human pose forecasting is a complex structured-data sequence-modelling task, which has
received increasing attention, also due to numerous potential applications. Research has …
received increasing attention, also due to numerous potential applications. Research has …
[图书][B] Neural networks and deep learning
CC Aggarwal - 2018 - Springer
“Any AI smart enough to pass a Turing test is smart enough to know to fail it.”–*** Ian
McDonald Neural networks were developed to simulate the human nervous system for …
McDonald Neural networks were developed to simulate the human nervous system for …
Back to mlp: A simple baseline for human motion prediction
This paper tackles the problem of human motion prediction, consisting in forecasting future
body poses from historically observed sequences. State-of-the-art approaches provide good …
body poses from historically observed sequences. State-of-the-art approaches provide good …
How to represent part-whole hierarchies in a neural network
G Hinton - Neural Computation, 2023 - direct.mit.edu
This article does not describe a working system. Instead, it presents a single idea about
representation that allows advances made by several different groups to be combined into …
representation that allows advances made by several different groups to be combined into …
Progressively generating better initial guesses towards next stages for high-quality human motion prediction
This paper presents a high-quality human motion prediction method that accurately predicts
future human poses given observed ones. Our method is based on the observation that a …
future human poses given observed ones. Our method is based on the observation that a …