Researchers have developed a compact, low-cost convolutional spectrometer that delivers lab-grade precision for applications ...

Abstract: The development of remote sensing images in recent years has made it possible to identify materials in inaccessible environments and study natural materials on a large scale. But ...

DBB is a powerful ConvNet building block to replace regular conv. It improves the performance without any extra inference-time costs. This repo contains the code for building DBB and converting it ...

Apple is introducing a new version of its system-level RAW image processing engine that uses machine learning to greatly ...

Because Krea relinquishes centralized control over the downstream deployment of its open weights, the contract legally binds ...

Soft robotics continues to push beyond the constraints of rigid mechanisms, offering adaptable solutions for grasping, ...

The key to more powerful plugins may be the graphics processor that you already have in your computer. We discover how three developers are making this happen right now When you purchase through links ...

Abstract: Deep learning (DL) has emerged as a focal point in addressing various challenges within the field of exploration seismology, prominently featuring applications in seismic data interpolation.

We explore the untapped potential of Kolmogorov-Anold Network (aka. KAN) in improving backbones for vision tasks. We investigate, modify and re-design the established U-Net pipeline by integrating the ...

For example, AI applications to medical diagnosis should be regulated very differently from AI applications to self-driving cars. U.S. National Academies report on AI and the Future of Work, study ...

This suggests that future work could continue to improve both the data and model levels—for example, by incorporating more real-world plant inspection samples to enhance cross-scene generalization, ...