Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...

RetinaDA unites six public fundus sets into a 512 × 512 macula-centered benchmark with built-in domain gaps, enabling ...

Deep learning (DL) is a type of artificial intelligence (AI) that utilizes artificial neural networks (ANNs) to process data through two or more layers, each of which can recognize complex features of ...

One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...

The seven-month programme is aimed at working professionals seeking to build production-ready artificial intelligence ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

A research team has developed a new hybrid artificial intelligence framework that can accurately estimate leaf nitrogen content without relying on labor-intensive field measurements.