Hybrid convolutional neural network ensemble for activity recognition in mobile phones
JH Chan, HJ Lim, NS Hoang, JH Lim, K Nguyen… - Soft Computing for …, 2021 - Springer
The increasing importance of human activity recognition in Ambient Assisted Living systems
(AAL) has brought a tremendous growth in research efforts in the field. Amongst these, the …
(AAL) has brought a tremendous growth in research efforts in the field. Amongst these, the …
Human activity recognition through ensemble learning of multiple convolutional neural networks
N Zehra, SH Azeem, M Farhan - 2021 55th Annual Conference …, 2021 - ieeexplore.ieee.org
Human Activity Recognition is a field concerned with the recognition of physical human
activities based on the interpretation of sensor data, including one-dimensional time series …
activities based on the interpretation of sensor data, including one-dimensional time series …
Human activity recognition with smartphone sensors using deep learning neural networks
CA Ronao, SB Cho - Expert systems with applications, 2016 - Elsevier
Human activities are inherently translation invariant and hierarchical. Human activity
recognition (HAR), a field that has garnered a lot of attention in recent years due to its high …
recognition (HAR), a field that has garnered a lot of attention in recent years due to its high …
A new CNN-LSTM architecture for activity recognition employing wearable motion sensor data: Enabling diverse feature extraction
Extracting representative features to recognize human activities through the use of
wearables is an area of on-going research. While hand-crafted features and machine …
wearables is an area of on-going research. While hand-crafted features and machine …
AttnHAR: Human Activity Recognition using Data Collected from Wearable Sensors
M Sethi, M Yadav, M Singh… - 2023 6th International …, 2023 - ieeexplore.ieee.org
In recent times, there has been a massive surge in demand for wearable sensing devices
which accurately decode human activities. These sensors are extensively used in …
which accurately decode human activities. These sensors are extensively used in …
Human Activity Recognition with smartphone sensors data using CNN-LSTM
A Sharma, P Singh, C Madhu, N Garg… - 2022 IEEE Conference …, 2022 - ieeexplore.ieee.org
Human activity recognition (HAR) utilizing wearable inertial sensors has nowadays become
a new research hotspot due to various advancements in sensor technology. Recently …
a new research hotspot due to various advancements in sensor technology. Recently …
A robust human activity recognition system using smartphone sensors and deep learning
In last few decades, human activity recognition grabbed considerable research attentions
from a wide range of pattern recognition and human–computer interaction researchers due …
from a wide range of pattern recognition and human–computer interaction researchers due …
A deep learning approach for human activities recognition from multimodal sensing devices
Research in the recognition of human activities of daily living has significantly improved
using deep learning techniques. Traditional human activity recognition techniques often use …
using deep learning techniques. Traditional human activity recognition techniques often use …
A CNN based transfer learning model for automatic activity recognition from accelerometer sensors
Accelerometers are become ubiquitous and available in several devices such as
smartphones, smartwaches, fitness trackers, and wearable devices. Accelerometers are …
smartphones, smartwaches, fitness trackers, and wearable devices. Accelerometers are …
Human activity recognition using temporal convolutional network
Human activity recognition using wearable sensors is an area of interest for various domains
like healthcare, surveillance etc. Various approaches have been used to solve the problem …
like healthcare, surveillance etc. Various approaches have been used to solve the problem …