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Underwater object detection: architectures and algorithms–a comprehensive review
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 …
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
Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …
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
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 …
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
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 …
imbalance. The most inexpensive and efficient solution to alleviate this imbalance is to …
[HTML][HTML] Multimodal detection of epilepsy with deep neural networks
Epilepsy constitutes a chronic noncommunicable disease of the brain affecting
approximately 50 million people around the world. Most of the existing research initiatives …
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
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 …
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
This article proposes two novel modified techniques, namely Pythagorean fuzzy hybrid
Order of Preference by Similarity to an Ideal Solution (PFH-TOPSIS) method and …
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
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 …
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
Electroencephalogram (EEG) signals are non-linear and non-stationary in nature. The
phase-space representation (PSR) method is useful for analysing the non-linear …
phase-space representation (PSR) method is useful for analysing the non-linear …
Seizure detection algorithm based on improved functional brain network structure feature extraction
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 …
seizures is essential for treatment. A seizure detection method with the structure of functional …