All Outputs (18)

LLM-guided instance-level image manipulation with diffusion u-net cross-attention maps (2024)
Presentation / Conference Contribution

The advancement of text-to-image synthesis has introduced powerful generative models capable of creating realistic images from textual prompts. However, precise control over image attributes remains challenging, especially at the instance level. Whil... Read More about LLM-guided instance-level image manipulation with diffusion u-net cross-attention maps.

Leveraging deep reinforcement learning and healthcare devices for active travelling in smart cities (2024)
Journal Article

Smart cities are increasingly challenged by population growth and the environmental emissions of urban transportation systems, necessitating sustainable urban planning to improve public health, environmental quality, and overall urban livability. A n... Read More about Leveraging deep reinforcement learning and healthcare devices for active travelling in smart cities.

Cache sharing in UAV-enabled cellular network: A deep reinforcement learning-based approach (2024)
Journal Article

Caching content at base stations has proven effective at reducing transmission delays. This paper investigates the caching problem in a network of highly dynamic cache-enabled Unmanned Aerial Vehicles (UAVs), which serve ground users as aerial base s... Read More about Cache sharing in UAV-enabled cellular network: A deep reinforcement learning-based approach.

A contract theory-based incentive mechanism for UAV-enabled VR-based services in 5G and beyond (2023)
Journal Article

The proliferation of novel infotainment services such as Virtual Reality(VR)-based services has fundamentally changed the existing mobile networks. These bandwidth-hungry services expanded at a tremendously rapid pace, thus, generating a burden of da... Read More about A contract theory-based incentive mechanism for UAV-enabled VR-based services in 5G and beyond.

Joint communication, computation, and control for computational task offloading in vehicle-assisted multi-access edge computing (2022)
Journal Article

Future generation of Electric Vehicles (EVs) equipped with modern technologies will impose a significant burden on computation and communication to the network due to the vast extension of onboard infotainment services. To overcome this challenge, mu... Read More about Joint communication, computation, and control for computational task offloading in vehicle-assisted multi-access edge computing.

Multiple adversarial domains adaptation approach for mitigating adversarial attacks effects (2022)
Journal Article

Although neural networks are near achieving performance similar to humans in many tasks, they are susceptible to adversarial attacks in the form of a small, intentionally designed perturbation, which could lead to misclassifications. The best defense... Read More about Multiple adversarial domains adaptation approach for mitigating adversarial attacks effects.

PbCP: A profit-based cache placement scheme for next-generation IoT-based ICN networks (2022)
Journal Article

The large number of connected devices generating a massive amount of data in the emerging technologies such as the Internet of Things (IoT), will surpass the capabilities of the current Internet infrastructure. Therefore, it is essential to design a... Read More about PbCP: A profit-based cache placement scheme for next-generation IoT-based ICN networks.

Computing on wheels: A deep reinforcement learning-based approach (2022)
Journal Article

Future generation vehicles equipped with modern technologies will impose unprecedented computational demand due to the wide adoption of compute-intensive services with stringent latency requirements. The computational capacity of the next generation... Read More about Computing on wheels: A deep reinforcement learning-based approach.

ApplianceNet: A neural network based framework to recognize daily life activities and behavior in smart home using smart plugs (2022)
Journal Article

A smart plug can transform the typical electrical appliance into a smart multi-functional device, which can communicate over the Internet. It has the ability to report the energy consumption pattern of the attached appliance which offer the further a... Read More about ApplianceNet: A neural network based framework to recognize daily life activities and behavior in smart home using smart plugs.

Online service provisioning in NFV-enabled networks using deep reinforcement learning (2022)
Journal Article

In this paper, we study a Deep Reinforcement Learning (DRL) based framework for an online end-user service provisioning in a Network Function Virtualization (NFV)-enabled network. We formulate an optimization problem aiming to minimize the cost of ne... Read More about Online service provisioning in NFV-enabled networks using deep reinforcement learning.

A novel deep reinforcement learning-based approach for task-offloading in vehicular networks (2022)
Presentation / Conference Contribution

Next-generation vehicular networks will impose unprecedented computation demand due to the wide adoption of compute-intensive services with stringent latency requirements. Computational capacity of vehicular networks can be enhanced by integration of... Read More about A novel deep reinforcement learning-based approach for task-offloading in vehicular networks.

On the fairness of generative adversarial networks (GANs) (2022)
Presentation / Conference Contribution

Generative adversarial networks (GANs) are one of the greatest advances in AI in recent years. With their ability to directly learn the probability distribution of data and then sample synthetic realistic data. Many applications have emerged, using G... Read More about On the fairness of generative adversarial networks (GANs).

API security in large enterprises: Leveraging machine learning for anomaly detection (2021)
Presentation / Conference Contribution

Large enterprises offer thousands of micro-services applications to support their daily business activities by using Application Programming Interfaces (APIs). These applications generate huge amounts of traffic via millions of API calls every day, w... Read More about API security in large enterprises: Leveraging machine learning for anomaly detection.

A novel contract theory-based incentive mechanism for cooperative task-offloading in electrical vehicular networks (2021)
Journal Article

The proliferation of compute-intensive services in next-generation vehicular networks will impose an unprecedented computation demand to meet stringent latency and resource requirements. Vehicular edge or fog computing has been a widely adopted solut... Read More about A novel contract theory-based incentive mechanism for cooperative task-offloading in electrical vehicular networks.

On-device computational caching-enabled augmented reality for 5G and beyond: A contract-theory-based incentive mechanism (2021)
Journal Article

Recently, we have witnessed an increasing demand in augmented reality (AR)-based fifth-generation (5G) and beyond applications, such as smart gaming, smart navigation, smart military wearable, and smart industries. These AR-based applications require... Read More about On-device computational caching-enabled augmented reality for 5G and beyond: A contract-theory-based incentive mechanism.

Adversarial reconstruction loss for domain generalization (2021)
Journal Article

The biggest fear when deploying machine learning models to the real world is their ability to handle the new data. This problem is significant especially in medicine, where models trained on rich high-quality data extracted from large hospitals do no... Read More about Adversarial reconstruction loss for domain generalization.

Blockchain for IoT-based smart cities: Recent advances, requirements, and future challenges (2021)
Journal Article

A remarkable interest in the Internet of Things (IoT)-based smart cities from both academia and industry has been observed in recent years. Smart cities can offer various smart applications such as intelligent transportation, industry 4.0, smart bank... Read More about Blockchain for IoT-based smart cities: Recent advances, requirements, and future challenges.

Internet of things forensics: Recent advances, taxonomy, requirements, and open challenges (2018)
Journal Article

The explosive growth of smart objects and their dependency on wireless technologies for communication increases the vulnerability of Internet of Things (IoT) to cyberattacks. Cyberattacks faced by IoT present daunting challenges to digital forensic e... Read More about Internet of things forensics: Recent advances, taxonomy, requirements, and open challenges.