Reconstructing Diffusion Model for Virality Detection in News Spread Networks

Jain, Kritika; Garg, Ankit; Jain, Somya

doi:10.4018/ijkss.2019010102

Cited by 4 publications

(2 citation statements)

References 24 publications

(2 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The rise of Artificial Intelligence (AI) has improved many conventional applications, systems and tasks in several domains such as, autonomous cars, smart cities, smartphones, smart truck distribution [6] and pandemic detection [7].…”

Section: Literature Reviewmentioning

confidence: 99%

Real-Time Airborne Target Tracking using DeepSort Algorithm and Yolov7 Model

Ghazlane,

Alaoui,

Medomi

et al. 2024

IJACSA

View full text Add to dashboard Cite

In light of the explosive growth of drones, it is more critical than ever to strengthen and secure aerial security and privacy. Drones are used maliciously by exploiting some gaps in artificial intelligence and cybersecurity. Airborne target detection and tracking tasks have gained paramount importance in various domains, encompassing surveillance, security, and traffic management. As airspace security systems aiming to regulate drone activities, anti-drones leverage mostly artificial intelligence and computer vision advances in the used detection and tracking models to perform effectively and accurately airborne target detection, identification, and tracking. The reliability of the anti-drone systems relies mostly on the ability of the incorporated models to satisfy an optimal compromise between speed and performance in terms of inference speed and used detection evaluation metrics since the system should recognize the targets effectively and rapidly to take appropriate actions regarding the target. This research article explores the efficacy of DeepSort algorithm coupled with YOLOv7 model in detecting and tracking five distinct airborne targets namely, drones, birds, airplanes, daytime frames, and buildings across diverse contexts. The used DeepSort and Yolov7 models aim to be used in anti-drone systems to detect and track the most encountered airborne targets to reinforce airspace safety and security. The study conducts a comparative analysis of tracking performance under different scenarios to evaluate the algorithm's versatility, robustness, and accuracy. The experimental results show the effectiveness of the proposed approach.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Real-Time Airborne Target Tracking using DeepSort Algorithm and Yolov7 Model

Ghazlane,

Alaoui,

Medomi

et al. 2024

IJACSA

View full text Add to dashboard Cite

show abstract

“…Based on the two-dimensional square, Jain et al proposed the general model of the WS small-world model. Yangbo et al put forward the small-world network model based on individual choices [12]. Dong and Cao proposed a small-world network model based on a geographic choice of optimal connection mechanism [13].…”

Section: Related Workmentioning

confidence: 99%

News Hotspot Event Diffusion Mechanism Based on Complex Network

Guo

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The wide range of social hot news events on the Internet has made the Internet have a great impact on the public. However, there are few studies on Internet information. In order to improve the efficiency of user network information dissemination of Internet information based on complex network theory and model simulation, this paper makes a more in-depth study on information dissemination on the Internet, constructs a complex network of Internet information dissemination, and analyzes the static topology and dynamic evolution process of the network. Using the attention relationship between Internet users, the Internet information dissemination network, degree, and path were used to select multiple indicators. The static topology of the network is analyzed by using the complex network theory. The study found that the complex network of Internet information is different from other complex networks. The influencing factors of network dynamic evolution are studied from three aspects: overall structure, local structure, and time constraints. The evolution trend of different forms and overall network nodes in the evolution process was explored, and the network dynamic evolution process model was constructed. Practice shows that the model can better describe the evolution process of network information dissemination in complex networks. The degree values of the two networks are positively correlated with the corresponding average clustering coefficients, and the networks have a significant hierarchy. The correlation between news hot events and network nodes is not as good as users’ attention to the network.

show abstract