64 citations
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41 papers
AutoCluster, AutoTopicModeling, AutoTrendAnalysis: A Complete AutoML Pipeline for Predicting Emerging Trends
Ahmed Abolfadl, Marwa Mahmoud Abla, Mervat Abu-Elkheir +1
Predicting emerging trends is vital for businesses, researchers, and policymakers; yet traditional approaches often lack scalability and adaptability. This paper presents a trend p…
Forecasting Technological Directions in Wireless Networks and Mobile Computing via AutoML Framework
Ahmed Abolfadl, Marwa Mahmoud, Basma Afifi +2
The exponential increase in scientific publications has driven the emergence of new trends. Accurate forecasting of these developments is essential for researchers and professional…
Network Distributed Multi-Agent Reinforcement Learning for Consensus Control of Quadcopters
Youssef Mahran, Zeyad Gamal, Aamir Ahmad +1
This paper proposes a Network Distributed Multi-Agent Reinforcement Learning (ND-MARL) framework for quadcopter consensus control. Compared to conventional multi-agent MARL formula…
Image Thresholding: Understanding Bias of Evaluation Metrics towards Specific Evaluation Functions
Eslam Hegazy, Mohamed Gabr
Multilevel image thresholding is widely used for segmentation in applications ranging from medical imaging to remote sensing. Classical objective functions, such as Otsu's between-…
From Prompts to Pavement: LMMs-based Agentic Behavior-Tree Generation Framework for Autonomous Vehicles
Omar Y. Goba, Ahmed Y. Gado, Catherine M. Elias +1
Autonomous vehicles (AVs) require adaptive behavior planners to navigate unpredictable, real-world environments safely. Traditional behavior trees (BTs) offer structured decision l…
Dynamic Entropy Tuning in Reinforcement Learning Low-Level Quadcopter Control: Stochasticity vs Determinism
Youssef Mahran, Zeyad Gamal, Ayman El-Badawy
This paper explores the impact of dynamic entropy tuning in Reinforcement Learning (RL) algorithms that train a stochastic policy. Its performance is compared against algorithms th…