Engineered tin dioxide nanosensors combined with deep learning enable precise gas classification, improving detection in ...

Studies leveraging NIR and CNNs report accuracies exceeding 95%, with some achieving perfect classification for pure fibers.

Matrox Imaging offers Design Assistant and MIL libraries to help enable rapid development with flowchart-based programming ...

With 98.4% accuracy in melanoma detection, SkinEHDLF demonstrates the potential of hybrid deep learning models in ...

In today’s digital transformation era, scientific inquiry is increasingly guided by computational tools that uncover intricate biological mechanisms. Sarika Kondra, along with co-authors Feng Chen, ...

E-beam inspection’s notorious sensitivity-throughput tradeoff has made comprehensive defect coverage with e-beam at these ...

Welcome to Learn with Jay – your go-to channel for mastering new skills and boosting your knowledge! Whether it’s personal ...

Build an image classifier using CNNs in Keras — this full implementation guides you line-by-line. #CNN #ImageClassification ...

Researchers made a technique that improves the trustworthiness of machine-learning models, which could help improve the accuracy and reliability of AI predictions for high-stakes settings such health ...

Mixture-of-Experts (MoE) models are revolutionizing the way we scale AI. By activating only a subset of a model’s components ...

Estimating the pose of hand-held objects is a critical and challenging problem in robotics and computer vision. While leveraging multi-modal RGB and depth data is a promising solution, existing ...

Alessandro Ingrosso, researcher at the Donders Institute for Neuroscience, has developed a new mathematical method in ...