M Srıdevı
Biographic Data
| ID | 10246675 |
|---|---|
| NAME | M Srıdevı |
| GIVEN NAMES | M |
| FAMILY NAME | Srıdevı |
| SIGNATURE | SRIDEVI M |
| AFFILIATIONS | National Institute of Technology Tiruchirappalli |
| ORCID | 0000-0003-0657-7188 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Face Warping Deepfake Detection and Localization in a Digital Video using Transfer Learning Approach
Generative AI (GenAI) can generate high-resolution and complex content mimicking the creativity of humans, thereby benefiting industries such as gaming, entertainment, and product design. In recent times, AI-generated fake videos, commonly referred to as deepfakes, have become more commonplace and convincing. An additional deepfake technique, face warping, uses digital processing to noticeably distort shapes on a face. Tracking such warping in im…
A Neural-Based Approach for Detecting the Situational Information From Twitter During Disaster
Twitter is widely considered an essential social media used during a disaster. For the past five years, there has been a great surge in the use of Twitter during the disaster. A large amount of useful information is posted on Twitter during an emergency, along with the users' sympathies and opinions. Therefore, a reliable methodology is needed for extracting useful information from the posted tweets during the disaster. This article is focused on…
Identification of medical resource tweets using Majority Voting-based Ensemble during disaster
Disaster damage assessment from the tweets using the combination of statistical features and informative words
Disaster damage assessment from the tweets using the combination of statistical features and informative words
Identification of medical resource tweets using Majority Voting-based Ensemble during disaster
A Neural-Based Approach for Detecting the Situational Information From Twitter During Disaster
Twitter is widely considered an essential social media used during a disaster. For the past five years, there has been a great surge in the use of Twitter during the disaster. A large amount of useful information is posted on Twitter during an emergency, along with the users' sympathies and opinions. Therefore, a reliable methodology is needed for extracting useful information from the posted tweets during the disaster. This article is focused on…
Face Warping Deepfake Detection and Localization in a Digital Video using Transfer Learning Approach
Generative AI (GenAI) can generate high-resolution and complex content mimicking the creativity of humans, thereby benefiting industries such as gaming, entertainment, and product design. In recent times, AI-generated fake videos, commonly referred to as deepfakes, have become more commonplace and convincing. An additional deepfake technique, face warping, uses digital processing to noticeably distort shapes on a face. Tracking such warping in im…
Artificial Intelligence (4 works) · Computer Science (4 works) · Public Relations and Crisis Communication (3 works) · Convolutional neural network (2 works) · Machine learning (2 works) · Misinformation and Its Impacts (2 works) · Sentiment Analysis and Opinion Mining (2 works) · Situation awareness (2 works) · Situational ethics (2 works) · Social media (2 works)