Artificial Intelligence (AI) is revolutionizing the dynamics of technological advancement in the field of medical imaging, ...

Over nine days, Elon Musk’s Grok chatbot generated and posted 4.4 million images, of which at least 41 percent were sexualized images of women.

Adversarial examples—images subtly altered to mislead AI systems—are used to test the reliability of deep neural networks.

The University of North Florida has once again been recognized for its sustained commitment to community partnership, earning ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Develop an AI-based image classification system using CNN and transfer learning. The project includes data preprocessing, model training, fine-tuning, evaluation with precision, recall, and F1-score, ...

Real-time image classification using a pre-trained ResNet18 model. Upload and preview images directly in the browser. Modular and extensible architecture for adding new models or classes. Modern, ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...

Abstract: Objective: Deep neural networks are widely used in the field of optical coherence tomography (OCT) to screen some common retinal diseases. However, for rare diseases with fewer cases for ...