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Brain tumor detection with integrating traditional and computational intelligence approaches across diverse imaging modalities-Challenges and future directions
Brain tumor segmentation and classification play a crucial role in the diagnosis and
treatment planning of brain tumors. Accurate and efficient methods for identifying tumor …
treatment planning of brain tumors. Accurate and efficient methods for identifying tumor …
[HTML][HTML] A federated learning approach to breast cancer prediction in a collaborative learning framework
Breast cancer continues to pose a substantial worldwide public health concern,
necessitating the use of sophisticated diagnostic methods to enable timely identification and …
necessitating the use of sophisticated diagnostic methods to enable timely identification and …
Intrusion detection using machine learning techniques: an experimental comparison
Due to an exponential increase in the number of cyber-attacks, the need for improved
Intrusion Detection Systems (IDS) is apparent than ever. In this regard, Machine Learning …
Intrusion Detection Systems (IDS) is apparent than ever. In this regard, Machine Learning …
Electroencephalography (EEG) based neonatal sleep staging and detection using various classification algorithms
Automatic sleep staging of neonates is essential for monitoring their brain development and
maturity of the nervous system. EEG based neonatal sleep staging provides valuable …
maturity of the nervous system. EEG based neonatal sleep staging provides valuable …
Single-Channel EEG data analysis using a multi-branch CNN for neonatal sleep staging
Neonatal sleep staging is crucial for understanding infant brain development and assessing
neurological health. This study explores the optimal electrode configuration to reduce …
neurological health. This study explores the optimal electrode configuration to reduce …
[HTML][HTML] Recurrent nonsymmetric deep auto encoder approach for network intrusion detection system
R Kalpana - Measurement: Sensors, 2022 - Elsevier
An important part of network security is a network intrusion detection system (NIDS). In the
face of the need for new networks, there are issues regarding the feasibility of traditional …
face of the need for new networks, there are issues regarding the feasibility of traditional …
Ensemble-based effective diagnosis of thyroid disorder with various feature selection techniques
Thyroid illness is characterized by the abnormal growth of thyroid tissue on the thyroid
gland's periphery. Hyperthyroidism and hypothyroidism are the two most common types of …
gland's periphery. Hyperthyroidism and hypothyroidism are the two most common types of …
[PDF][PDF] Scalable Anomaly Detection Frameworks for Network Traffic Analysis in cybersecurity using Machine Learning Approaches
M Gopalsamy - Int. J. Curr. Eng. Technol, 2022 - researchgate.net
The capacity to detect facts or observations that differ from what is normally thought of by
domain experts is crucial for many contemporary applications. These outliers may be …
domain experts is crucial for many contemporary applications. These outliers may be …
A Comparative Performance Analysis of Machine Learning Models for Intrusion Detection Classification.
The importance of cybersecurity in contemporary society cannot be inflated, given the
substantial impact of networks on various aspects of daily life. Traditional cybersecurity …
substantial impact of networks on various aspects of daily life. Traditional cybersecurity …
Методика обнаружения аномалий и кибератак на основе интеграции методов фрактального анализа и машинного обучения
ИВ Котенко, ИБ Саенко, ОС Лаута… - Информатика и …, 2022 - mathnet.ru
В современных сетях передачи данных для постоянного мониторинга сетевого
трафика и обнаружения в нем аномальной активности, а также идентификации и …
трафика и обнаружения в нем аномальной активности, а также идентификации и …