Vehicle detection and classification using an ensemble of EfficientDet and YOLOv8.

With the rapid increase in vehicle numbers, efficient traffic management has become a critical challenge for society. Traditional methods of vehicle detection and classification often struggle with the diverse characteristics of vehicles, such as varying shapes, colors, edges, shadows, and textures. To address this, we proposed an innovative ensemble method that combines two state-of-the-art deep learning models EfficientDet and YOLOv8.

MCred: multi-modal message credibility for fake news detection using BERT and CNN.

Online social media enables low cost, easy access, rapid propagation, and easy communication of information, including spreading low-quality fake news. Fake news has become a huge threat to every sector in society, and resulting in decrements in the trust quotient for media and leading the audience into bewilderment. In this paper, we proposed a new framework called essage ibility (MCred) for fake news detection that utilizes the benefits of local and global text semantics.

XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks.

COVID-19 (also known as SARS-COV-2) pandemic has spread in the entire world. It is a contagious disease that easily spreads from one person in direct contact to another, classified by experts in five categories: asymptomatic, mild, moderate, severe, and critical. Already more than 66 million people got infected worldwide with more than 22 million active patients as of 5 December 2020 and the rate is accelerating.