Improved EEG-based emotion recognition through information enhancement in connectivity feature map
Electroencephalography (EEG), despite its inherited complexity, is a preferable brain signal
for automatic human emotion recognition (ER), which is a challenging machine learning task …
for automatic human emotion recognition (ER), which is a challenging machine learning task …
Rotor fault diagnosis method using CNN-Based transfer learning with 2D sound spectrogram analysis
H Jung, S Choi, B Lee - Electronics, 2023 - mdpi.com
This study discusses a failure detection algorithm that uses frequency analysis and artificial
intelligence to determine whether a rotor used in an industrial setting has failed. A rotor is a …
intelligence to determine whether a rotor used in an industrial setting has failed. A rotor is a …
Explainable indoor localization of BLE devices through RSSI using recursive continuous wavelet transformation and XGBoost classifier
Indoor localization systems with higher precision and integrity are being highly demanded
because of their numerous applications in superstores, smart homes, smart cities, elderly …
because of their numerous applications in superstores, smart homes, smart cities, elderly …
Brain driving: personalizing vehicle speed with DR-EEG decoding and situational embeddings
Driving is a complex and personalized endeavor that entails the brain processing sensory
information amidst continuously changing situations. Here, we sought to explore the …
information amidst continuously changing situations. Here, we sought to explore the …
[HTML][HTML] A machine learning-based decision support system for temporal human cognitive state estimation during online education using wearable physiological …
Over the last decade, there has been a considerable increase in the popularity of online
education. As a result, the online learning or e-learning industry has flourished, providing …
education. As a result, the online learning or e-learning industry has flourished, providing …
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis: A machine learning approach
Mosquito-borne diseases present considerable risks to the health of both animals and
humans. Aedes aegypti mosquitoes are the primary vectors for numerous medically …
humans. Aedes aegypti mosquitoes are the primary vectors for numerous medically …
[HTML][HTML] Unlocking Security for Comprehensive Electroencephalogram-Based User Authentication Systems
With recent significant advancements in artificial intelligence, the necessity for more reliable
recognition systems has rapidly increased to safeguard individual assets. The use of brain …
recognition systems has rapidly increased to safeguard individual assets. The use of brain …
[HTML][HTML] Recognition of Sheep Feeding Behavior in Sheepfolds using Fusion Spectrogram depth features and acoustic features
Y Yu, W Zhu, X Ma, J Du, Y Liu, L Gan, X An, H Li… - Animals, 2024 - mdpi.com
In precision feeding, non-contact and pressure-free monitoring of sheep feeding behavior is
crucial for health monitoring and optimizing production management. The experimental …
crucial for health monitoring and optimizing production management. The experimental …
Machine Learning and Electroencephalogram Signal based Diagnosis of Dipression
Depression is a psychological condition which hampers day to day activity (Thinking,
Feeling or Action). The early detection of this illness will help to save many lives because it …
Feeling or Action). The early detection of this illness will help to save many lives because it …
OEDL: an optimized ensemble deep learning method for the prediction of acute ischemic stroke prognoses using union features
W Ye, X Chen, P Li, Y Tao, Z Wang, C Gao… - Frontiers in …, 2023 - frontiersin.org
Background Early stroke prognosis assessments are critical for decision-making regarding
therapeutic intervention. We introduced the concepts of data combination, method …
therapeutic intervention. We introduced the concepts of data combination, method …