Human activity classification using deep learning based on 3D ...

This paper proposes a novel method of classifying nine activities based on the movement features of changes in joint distance using Euclidean on the order of ...

Deep Learning for Human Activity Recognition on 3D Human Skeleton

In this paper, we perform a full survey on using deep learning to recognize human activity based on three-dimensional (3D) human skeleton data as input.

(PDF) Deep Learning-Based for Human Activity Recognition on 3D ...

In particular, we also carried out a comparative study on HAR based on a 3D human skeleton on the KLHA3D 102 and KLYOGA3D datasets. At the same ...

Human activity classification using deep learning based on 3D ...

Semantic Scholar extracted view of "Human activity classification using deep learning based on 3D motion feature" by Endang Sri Rahayu et al.

Human activity classification using deep learning based on 3D ...

Request PDF | Human activity classification using deep learning based on 3D motion feature | Human activity classification is needed to support various ...

Detecting human activity types from 3D posture data using deep ...

Classifying videos with convolutional neural networks (CNNs) can introduce some difficulties. Training performance of video-based data with CNN models is ...

Deep Learning-Based Human Activity Real-Time Recognition for ...

used CNN and accelerometer data to recognize human activities in real-time [26]. Wang, K. et al. used re-configurable convolutional neural networks for 3D human ...

A Close Look into Human Activity Recognition Models using Deep ...

BLSTM-RNN based 3D Gesture Classification. In Artificial Neural. Networks and Machine Learning, ICANN 2013, 23rd International. Conference on Artificial ...

STAR-3D: A Holistic Approach for Human Activity Recognition in the ...

To our knowledge, STAR-3D is the first deep-learning-based method to classify students' and teachers' activities in a classroom environment;. This model can ...

Performance evaluation of deep learning techniques for human ...

In this paper, a human activity recognition-based 3D Long-term Recurrent Convolutional Network (3DLRCN) ... makes them easier to recognize and classify compared ...

An improved human activity recognition technique based ... - Nature

Machine learning (ML) and deep learning (DL) are subsets of AI. ML and DL might be implicated during the classification of images to get better ...

HARNet in deep learning approach—a systematic survey - Nature

Activities-based Action Recognition typically refers to the recognition and classification of human actions based on various activities ...

Human activity classification using deep learning based on ... - OUCI

Human activity classification using deep learning based on 3D motion feature ; Journal: Machine Learning with Applications, 2023, p. 100461 ; Publisher: Elsevier ...

3D Human Activity Recognition with Reconfigurable Convolutional ...

Imagenet classification with deep convolutional neural networks. In ... E(2024)Multimodal vision-based human action recognition using deep learning ...

Human Activity Recognition via Hybrid Deep Learning Based Model

An online classification technique using a variable-length maximum entropy Markov model (MEMM) based on likelihood probabilities is utilized for ...

A Review of Deep Learning-based Human Activity Recognition on ...

Different types of research have been done on video data using Artificial Intelligence (AI) deep learning techniques. Most of them are behavior analysis, ...

A Deep Learning‐Based Framework for Human Activity Recognition ...

This framework proposes a detailed methodology for data preprocessing, feature mining, and deep learning techniques application.

Human activity recognition in artificial intelligence framework

Buffelli D, Vandin F (2020) Attention-based deep learning framework for human activity recognition with user adaptation. arXiv, 2020 ...

A Hybrid Deep Learning-Based Approach for Human Activity ...

Human Activity Recognition (HAR) is a branch of computer science that uses raw time-series data information from embedded smartphone sensors and wearable ...

A Deep Learning Approach to Human Activity Recognition Based on ...

This paper constructs a CNN model and modify the convolution kernel to adapt the characteristics of tri-axial acceleration signals, and shows that the CNN ...