Adversarially-Resilient Deep Learning Framework for Detecting Evasive Cyber Threats in Network Traffic

Nasser Alsharif

#adversarial #deep Learning #IDS #network traffic #cyber threats

Machine Learning Perspective Sattam Almatarneh

Dept. Data Science and AI Zarqa UniversityZarqa,Jordan

#Islamic architecture #deep learning #machine learning classifiers #Histogram of Oriented Gradients (HOG) #LocalBinary Patterns (LBP) #Convolutional Neural Networks (CNNs) #image classificationReceived DD Month YYYY; accepted DD Month YYYYhttps://doi

Pattern Recognition in Islamic Architecture: Machine Learning Perspective

Sattam Almatarneh,Noura Qazza,Ahmad Al Smadi

#Islamic architecture #deep learning #machine learning classifiers #Histogram of Oriented Gradients (HOG) #LocalBinary Patterns (LBP) #Convolutional Neural Networks (CNNs) #image classificationReceived January 05 #2025; accepted March 15 #2025https://doi

Inflammatory Bowel Disease Detection Using Machine Learning Techniques

Veerender Aerranagula,Raju Bhukya

#Bowel disease #crohn’s disease #machine learning

Exploring the Intersection of Information Theory and Machine Learning

Yousef Jaradat,Mohammad Masoud,Ahmad Manasrah,Mohammad Alia,Khalid Suwais,Sally Almanasra

#Information theory #machine learning #entropy #mutual information #information bottleneck

Hybrid CNN Xception and Long Short-Term Memory Model for the Detection of Interpersonal Violence in Videos

David Calderon-Vilca,Kent Cuadros-Ramos,Sergio Valcarcel-Ascencios,Igor Aguilar-Alonso

#Image processing #LSTM #patterns of violence #violence detection #xception

An Improved Taylor Hyperbolic Tangent and Sigmoid Activations for Avoiding Vanishing Gradients in Recurrent Neural Nets

Tirupati Gullipalli,Krishna Murali,Srinivasa Peri

#Vanishing gradient #taylor expansion #functional approximation #sigmoid #hyperbolic tangent #neural networks

Exploring the Intersection of Information Theory and Machine Learning

Yousef Jaradat,Mohammad Masoud,Ahmad Manasrah,Mohammad Alia,Khalid Suwais,Sally Almanasra

#Information theory #machine learning #entropy #mutual information #information bottleneck

Hybrid CNN Xception and Long Short-Term Memory Model for the Detection of Interpersonal Violence in Videos

David Calderon-Vilca,Kent Cuadros-Ramos,Sergio Valcarcel-Ascencios,Igor Aguilar-Alonso

#Image processing #LSTM #patterns of violence #violence detection #xception

An Improved Taylor Hyperbolic Tangent and Sigmoid Activations for Avoiding Vanishing Gradients in Recurrent Neural Nets

Tirupati Gullipalli,Krishna Murali,Srinivasa Peri

#Vanishing gradient #taylor expansion #functional approximation #sigmoid #hyperbolic tangent #neural networks

Federated Graph Neural Networks for Dynamic IoT Collaboration Optimization in Smart Home Environments

Cheng Zhang,Yuanquan Zhong

#IoT device collaboration #graph neural network #federated learning #graph structure #smart home

Neural Networks and Sentiment Features for Extremist Content Detection in Arabic Social Media

Hanen Himdi,Fatimah Alhayan,Khaled Shaalan

#BERT #sentiment analysis #deep learning #transformer-based models

Neural Networks and Sentiment Features for Extremist Content Detection in Arabic Social Media

Hanen Himdi,Fatimah Alhayan,Khaled Shaalan

#BERT #sentiment analysis #deep learning #transformer-based models

Integrating Multiplex Heterogeneous Network for Knowledge Tracing

Liqing Qiu,Si’ao Sun

#Knowledge tracing #multiplex heterogeneous networks #graph representation learning #pre-trained embeddings #graph convolutional networks

Multicasting Strategies for Increasing Network Efficiency in 5G Using Deep Learning

Wael AlZoubi,Hazem Hatamleh

#Multicasting #network performance #artificial intelligence #deep Q-networks #deep reinforcement learning #quality of service

Fuzzy Speech Recognition Algorithm Based on Continuous Density Hidden Markov Model and Self Organizing Feature Map

Yanning Zhang,Lei Ma,Yunwei Li

#Speech recognition #wiener filter #Mel-frequency cepstrum coefficient #continuous hidden Markov model #self-organizing feature neural network