Underwater object detection: architectures and algorithms–a comprehensive review

S Fayaz, SA Parah, GJ Qureshi - Multimedia Tools and Applications, 2022‏ - Springer
Underwater object detection is an essential step in image processing and it plays a vital role
in several applications such as the repair and maintenance of sub-aquatic structures and …

Machine learning algorithms for epilepsy detection based on published EEG databases: A systematic review

A Miltiadous, KD Tzimourta, N Giannakeas… - IEEE …, 2022‏ - ieeexplore.ieee.org
Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies

A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022‏ - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …

Deep sequence to sequence Bi-LSTM neural networks for day-ahead peak load forecasting

N Mughees, SA Mohsin, A Mughees… - Expert Systems with …, 2021‏ - Elsevier
The power industry is currently facing the problem of an electricity supply–demand
imbalance. The most inexpensive and efficient solution to alleviate this imbalance is to …

[HTML][HTML] Multimodal detection of epilepsy with deep neural networks

L Ilias, D Askounis, J Psarras - Expert Systems with Applications, 2023‏ - Elsevier
Epilepsy constitutes a chronic noncommunicable disease of the brain affecting
approximately 50 million people around the world. Most of the existing research initiatives …

[HTML][HTML] An efficient segmentation and classification system in medical images using intuitionist possibilistic fuzzy C-mean clustering and fuzzy SVM algorithm

CL Chowdhary, M Mittal, KP, PA Pattanaik… - Sensors, 2020‏ - mdpi.com
The herpesvirus, polyomavirus, papillomavirus, and retrovirus families are associated with
breast cancer. More effort is needed to assess the role of these viruses in the detection and …

Risk evaluation in failure modes and effects analysis: hybrid TOPSIS and ELECTRE I solutions with Pythagorean fuzzy information

M Akram, A Luqman, JCR Alcantud - Neural Computing and Applications, 2021‏ - Springer
This article proposes two novel modified techniques, namely Pythagorean fuzzy hybrid
Order of Preference by Similarity to an Ideal Solution (PFH-TOPSIS) method and …

A hybrid deep learning approach for epileptic seizure detection in EEG signals

I Ahmad, X Wang, D Javeed, P Kumar… - IEEE Journal of …, 2023‏ - ieeexplore.ieee.org
Early detection and proper treatment of epilepsy is essential and meaningful to those who
suffer from this disease. The adoption of deep learning (DL) techniques for automated …

Epileptic-seizure classification using phase-space representation of FBSE-EWT based EEG sub-band signals and ensemble learners

A Anuragi, DS Sisodia, RB Pachori - Biomedical signal processing and …, 2022‏ - Elsevier
Electroencephalogram (EEG) signals are non-linear and non-stationary in nature. The
phase-space representation (PSR) method is useful for analysing the non-linear …

Seizure detection algorithm based on improved functional brain network structure feature extraction

L Jiang, J He, H Pan, D Wu, T Jiang, J Liu - Biomedical Signal Processing …, 2023‏ - Elsevier
Epilepsy is one of the most common neurological disorders. Accurate detection of epileptic
seizures is essential for treatment. A seizure detection method with the structure of functional …