Authors : Khandakar Rabbi Ahmed, Md Sayham Khan, Md Anisur Rahman Chowdhury, Shah Tawkir Nesar, Md Afjal Hosien, Md Razaul Karim, Nasrin Sultana
Publication date : 2025/7/31
Conference : 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN)
Pages : 1-6
Publisher : IEEE
Description : TheThe rapid dissemination of misinformation on internet media severely undermines public opinion and decision- making. This study introduces a multimodal artificial intelligence approach that integrates computer vision (CV) and natural language processing (NLP) to identify misinformation. This methodology integrates deep learning vision models such as ResNet for image validation with transformer-based natural language processing models like BERT, RoBERTa, and GPT for textual examination, in contrast to traditional single-modal approaches. A complex fusion method connects textual and visual modalities, allowing a complete fact-checking system. Extensive testing on benchmark datasets shows that our methodology is better than conventional ones in accuracy, robustness, and efficiency in spotting altered or deceptive material. The suggested model increases misinformation detection using improved …
Total citations : Cited by 23
Scholar articles :
KR Ahmed, MS Khan, MAR Chowdhury, ST Nesar… – 2025 International Conference on Quantum Photonics …, 2025