Approaches to multi-objective feature selection: a systematic literature review
Feature selection has gained much consideration from scholars working in the domain of
machine learning and data mining in recent years. Feature selection is a popular problem in …
machine learning and data mining in recent years. Feature selection is a popular problem in …
A review of dimensionality reduction techniques for efficient computation
S Velliangiri, S Alagumuthukrishnan - Procedia Computer Science, 2019 - Elsevier
Dimensionality Reduction (DR) is the pre-processing step to remove redundant features,
noisy and irrelevant data, in order to improve learning feature accuracy and reduce the …
noisy and irrelevant data, in order to improve learning feature accuracy and reduce the …
Multi-input CNN-GRU based human activity recognition using wearable sensors
Abstract Human Activity Recognition (HAR) has attracted much attention from researchers in
the recent past. The intensification of research into HAR lies in the motive to understand …
the recent past. The intensification of research into HAR lies in the motive to understand …
A multibranch CNN-BiLSTM model for human activity recognition using wearable sensor data
Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
Pattern identification of different human joints for different human walking styles using inertial measurement unit (IMU) sensor
A bipedal walking robot is a kind of humanoid robot. It is suppose to mimics human behavior
and designed to perform human specific tasks. Currently, humanoid robots are not capable …
and designed to perform human specific tasks. Currently, humanoid robots are not capable …
RNN/LSTM with modified Adam optimizer in deep learning approach for automobile spare parts demand forecasting
KK Chandriah, RV Naraganahalli - Multimedia Tools and Applications, 2021 - Springer
The spare parts demand forecasting is very much essential for the organizations to minimize
the cost and prevent the stock outs. The demand of spare parts/car sales distribution is an …
the cost and prevent the stock outs. The demand of spare parts/car sales distribution is an …
An optimized hybrid deep learning model using ensemble learning approach for human walking activities recognition
Recent advancements in edge computing devices motivate us to develop a sustainable and
reliable technique for multiple gait activities recognition using wearable sensors. This …
reliable technique for multiple gait activities recognition using wearable sensors. This …
Fusion of multi-sensor-based biomechanical gait analysis using vision and wearable sensor
V Bijalwan, VB Semwal, TK Mandal - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
The purpose of this research work is to investigate the biomechanics of pelvis, hip, knee,
and ankle joint motion using a Kinect sensor & inertial measurement unit (IMU) sensor …
and ankle joint motion using a Kinect sensor & inertial measurement unit (IMU) sensor …
HDL-PSR: Modelling spatio-temporal features using hybrid deep learning approach for post-stroke rehabilitation
Physiotherapy exercises like extension, flexion, and rotation are an absolute necessity for
patients of post stroke rehabilitation (PSR). A physiotherapist uses many techniques to …
patients of post stroke rehabilitation (PSR). A physiotherapist uses many techniques to …
[HTML][HTML] Human activity recognition from sensor data using spatial attention-aided CNN with genetic algorithm
A Sarkar, SKS Hossain, R Sarkar - Neural Computing and Applications, 2023 - Springer
Capturing time and frequency relationships of time series signals offers an inherent barrier
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …