SSH-brute force attack detection model based on deep learning

SK Wanjau, GM Wambugu, GN Kamau - 2021 - repository.mut.ac.ke
The rising number of malicious threats on computer networks and Internet services owing to
a large number of attacks makes the network security be at incessant risk. One of the …

A Survey on Deep Learning Methods in Image Analytics

PK Vishwakarma, N Jain - … of Data Analytics and Management: ICDAM …, 2022 - Springer
The domain of machine learning (ML) is at bright phase as deep learning (DL) gradually
turns into pioneer in this sphere. DL utilizes numerous covers to address the reflections of …

[HTML][HTML] Atmospheric turbulence study with deep machine learning of intensity scintillation patterns

AM Vorontsov, MA Vorontsov, GA Filimonov… - Applied Sciences, 2020 - mdpi.com
Featured Application Atmospheric remote sensing, directed energy, free-space laser
communication, adaptive optics, lidars, active imaging, optical surveillance. Abstract A new …

[HTML][HTML] CryptoDL: Predicting dyslexia biomarkers from encrypted neuroimaging dataset using energy-efficient residue number system and deep convolutional neural …

OL Usman, RC Muniyandi - Symmetry, 2020 - mdpi.com
The increasing availability of medical images generated via different imaging techniques
necessitates the need for their remote analysis and diagnosis, especially when such …

[HTML][HTML] The automatic detection of cognition using eeg and facial expressions

M El Kerdawy, M El Halaby, A Hassan, M Maher… - Sensors, 2020 - mdpi.com
Detecting cognitive profiles is critical to efficient adaptive learning systems that automatically
adjust the content delivered depending on the learner's cognitive states and skills. This …