An ensemble deep learning model for human activity analysis using wearable sensory data
Lately, the continuous temporal data from motion sensors in wearable devices has been
great interest for the research community due to its demand for analyzing human activities in …
great interest for the research community due to its demand for analyzing human activities in …
Human activity recognition: A comprehensive review
Abstract Human Activity Recognition (HAR) is a highly promising research area meant to
automatically identify and interpret human behaviour using data received from sensors in …
automatically identify and interpret human behaviour using data received from sensors in …
Optimal soft open point placement and open switch position selection simultaneously for power loss reduction on the electric distribution network
Network reconfiguration through the selection of open switch positions on the electric
distribution network (EDN) is an effective solution to reduce power loss on the EDN …
distribution network (EDN) is an effective solution to reduce power loss on the EDN …
[HTML][HTML] Gastrovrg: Enhancing early screening in gastrointestinal health via advanced transfer features
The accurate classification of endoscopic images is a challenging yet critical task in medical
diagnostics, which directly affects the treatment and management of Gastrointestinal …
diagnostics, which directly affects the treatment and management of Gastrointestinal …
[HTML][HTML] A DCNN-LSTM based human activity recognition by mobile and wearable sensor networks
Abstract Systems for recognizing human activities are being developed as part of a larger
framework that will allow for continuous monitoring of human behavior in intelligent home …
framework that will allow for continuous monitoring of human behavior in intelligent home …
A wearing orientation-independent electromagnetic self-powered sensor for human activity recognition based on biomechanical energy scavenging
Self-powered human activity recognition (HAR) using vibration energy harvesters attracts
broad interest in wearable electronics. To address the challenge of making such sensors …
broad interest in wearable electronics. To address the challenge of making such sensors …
A Swin transformer and MLP based method for identifying cherry ripeness and decay
K Song, J Yang, G Wang - Frontiers in Physics, 2023 - frontiersin.org
Cherries are a nutritionally beneficial and economically significant crop, with fruit ripeness
and decay (rot or rupture) being critical indicators in the cherry sorting process. Therefore …
and decay (rot or rupture) being critical indicators in the cherry sorting process. Therefore …
CoTea: Collaborative teaching for low-resource named entity recognition with a divide-and-conquer strategy
Low-resource named entity recognition (NER) aims to identify entity mentions when training
data is scarce. Recent approaches resort to distant data with manual dictionaries for …
data is scarce. Recent approaches resort to distant data with manual dictionaries for …
A Method of Self-Supervised Denoising and Classification for Sensor-Based Human Activity Recognition
L Lu, T Deng - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Human activity recognition (HAR) is an important subfield of pervasive computing and
pattern recognition. While researchers have achieved remarkable results in feature …
pattern recognition. While researchers have achieved remarkable results in feature …
Facial Emotion Recognition and Classification Using the Convolutional Neural Network‐10 (CNN‐10)
The importance of facial expressions in nonverbal communication is significant because
they help better represent the inner emotions of individuals. Emotions can depict the state of …
they help better represent the inner emotions of individuals. Emotions can depict the state of …