Key Takeaways Quick Summary Omnidirectional imaging, which captures a full 360-degree view of a scene, has been underexplored in stereo depth estimation due to a lack of suitable data. The Helvipad dataset addresses this gap by offering 40,000 frames from various indoor and outdoor scenes, captured with a top-bottom 360° camera setup and LiDAR sensors.…

Key Takeaways Quick Summary Convolutional neural networks (CNNs) are powerful tools for image classification but are often too large for resource-constrained hardware. Researchers have developed a pruning method using Conditional Mutual Information (CMI) to measure and rank the importance of features across network layers. This strategy enables selective removal of less critical components while preserving…

Key Takeaways Quick Summary Coronary artery disease (CAD) remains a leading cause of mortality, requiring effective screening tools like coronary artery calcium (CAC) scoring via CT scans. Researchers have addressed limitations of traditional models by introducing DINO-LG, an AI model using self-supervised learning with label guidance. Without requiring annotated datasets, the model detects calcifications with…