Multimodal classification: Current landscape, taxonomy and future directions
Multimodal classification research has been gaining popularity with new datasets in
domains such as satellite imagery, biometrics, and medicine. Prior research has shown the …
domains such as satellite imagery, biometrics, and medicine. Prior research has shown the …
A survey on physiological signal-based emotion recognition
Physiological signals are the most reliable form of signals for emotion recognition, as they
cannot be controlled deliberately by the subject. Existing review papers on emotion …
cannot be controlled deliberately by the subject. Existing review papers on emotion …
Multimodal fusion convolutional neural network with cross-attention mechanism for internal defect detection of magnetic tile
H Lu, Y Zhu, M Yin, G Yin, L Xie - IEEE Access, 2022 - ieeexplore.ieee.org
The internal defect detection of magnetic tile is extremely significant before mounting.
Currently, this task is completely realized by manual operation in the magnetic tile …
Currently, this task is completely realized by manual operation in the magnetic tile …
Synthetic ecg signal generation using probabilistic diffusion models
Deep learning image processing models have had remarkable success in recent years in
generating high quality images. Particularly, the Improved Denoising Diffusion Probabilistic …
generating high quality images. Particularly, the Improved Denoising Diffusion Probabilistic …
Multimodal multi-instance learning for long-term ECG classification
Recently, deep learning-based models have been widely used for electrocardiogram (ECG)
classification tasks. Most ECG signals are long-term time series that contain a large number …
classification tasks. Most ECG signals are long-term time series that contain a large number …
[HTML][HTML] Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram
Artificial Intelligence (AI) use in automated Electrocardiogram (ECG) classification has
continuously attracted the research community's interest, motivated by their promising …
continuously attracted the research community's interest, motivated by their promising …
Application of internet of things on the healthcare field using convolutional neural network processing
J Mohana, B Yakkala, S Vimalnath… - Journal of …, 2022 - Wiley Online Library
Population at risk can benefit greatly from remote health monitoring because it allows for
early detection and treatment. Because of recent advances in Internet‐of‐Things (IoT) …
early detection and treatment. Because of recent advances in Internet‐of‐Things (IoT) …
ECG classification for detecting ECG arrhythmia empowered with deep learning approaches
According to the World Health Organization (WHO) report, heart disease is spreading
throughout the world very rapidly and the situation is becoming alarming in people aged 40 …
throughout the world very rapidly and the situation is becoming alarming in people aged 40 …
Evaluating time series encoding techniques for predictive maintenance
Predictive Maintenance has become an important component in modern industrial
scenarios, as a way to minimize down-times and fault rate for different equipment. In this …
scenarios, as a way to minimize down-times and fault rate for different equipment. In this …
A systematic review on artificial intelligence-based techniques for diagnosis of cardiovascular arrhythmia diseases: challenges and opportunities
Cardiovascular health-related problem is a rapidly increasing integrated field concerning the
processing and fetching the information from cardiovascular systems for early detection and …
processing and fetching the information from cardiovascular systems for early detection and …