Analysis of Multimodality Fusion of Medical Image Segmentation Employing Deep Learning

Santhakumar, G.; Takale, Dattatray G.; Tyagi, Swati; Anitha, Raju; Tiwari, Mohit; Dhanraj, Joshuva Arockia

doi:10.1002/9781394197705.ch11

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Book2

Article1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Challenges and opportunities to integrate artificial intelligence in radiation oncology: a narrative review

Jeong,

Goh,

Kwak

2024

Ewha Med J

View full text Add to dashboard Cite

Challenges and opportunities to integrate artificial intelligence in radiation oncology: a narrative review

Jeong,

Goh,

Kwak

2024

Ewha Med J

View full text Add to dashboard Cite

Generative AI-Driven Security Frameworks for Web Engineering

Rana,

Bhambri

2024

Advances in Web Technologies and Engineering

View full text Add to dashboard Cite

The advent of Generative AI has triggered a paradigm shift across several domains, resulting in ground-breaking advances in text, picture, video, audio, and code production. However, this technical advancement has also increased cyber security intimidations, as hackers increasingly use Generative AI in their harmful actions. Generative artificial intelligence (Gen-AI) and Huge words models (HWMs) are transforming businesses throughout the world. However, their enormous promise carries major hazards. It is critical to address the cyber security concerns related with Gen-AI. This aids organizations in comprehending the security implications of these technologies. This chapter will provide a complete Gen-AI security architecture and show how it may help us protect Gen-AI apps, models, and the whole Gen-AI ecosystem. This research attempts to define the many security vulnerabilities posed by Generative AI, identifying their manifestations across different application areas.

show abstract

Generative AI in Web Application Development

Rana,

Bhambri

2024

Advances in Web Technologies and Engineering

View full text Add to dashboard Cite

We lack knowledge of how User Experience and Performance practitioners, User Experience and Performance practitioner's teams, and businesses use Gen-AI and the issues they confront. We interviewed 24 User Experience and Performance practitioners from various firms and countries, all with different positions and levels of seniority. Our findings show that: 1 there is a major lack of Gen-AI corporate policy, with organizations informally advocating caution or delegating responsibility to individual workers; and 2 User Experience and Performance practitioners require group-wide Gen-AI exercises. User Experience and Performance practitioners characteristically use Gen-AI independently, esteeming inscription-based responsibilities, but letter boundaries for plan -attentive behavior such as wire framing and prototyping; 3) User Experience and Performance practitioners advocate for improved Gen-AI educating to improve their ability to make effectual stimulate and assess production brilliance.

show abstract

Analysis of Multimodality Fusion of Medical Image Segmentation Employing Deep Learning

Cited by 3 publications

References 30 publications

Challenges and opportunities to integrate artificial intelligence in radiation oncology: a narrative review

Challenges and opportunities to integrate artificial intelligence in radiation oncology: a narrative review

Generative AI-Driven Security Frameworks for Web Engineering

Generative AI in Web Application Development

Contact Info

Product

Resources

About