We interact with digital images every single day, snapping photos, applying filters, and rendering 3D visualizations. But while the human eye sees colors, shapes, and depth, a computer sees something ...

Three-dimensional (3D) cultured neural networks that emulate the structures and computational principles of the brain could be of use in the development of brain-inspired computing and artificial ...

IBM Analog Hardware Acceleration Kit is an open source Python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence. ⚠️ This library ...

CIANNA is a general-purpose deep learning framework primarily developed and used for astronomical data analysis. Functionalities and optimizations are added based on relevance for astrophysical ...

Abstract: This article focuses on the problem of query by example spoken term detection (QbE-STD) in zero-resource scenario. State-of-the-art approaches primarily rely on dynamic time warping (DTW) ...

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...

Location of earthquakes is a primary task in seismology and microseismic monitoring, essential for almost any further analysis. Earthquake hypocenters can be determined by the inversion of arrival ...

Abstract: Detecting points of interest on 3D shapes is a fundamental research problem in geometry processing. Due to the complicated relationship between points of interest and their geometric ...

Dr. James McCaffrey of Microsoft Research presents a simple technique he has used with good success, previously unpublished and without a standard name. The goal of an ordinal classification problem ...

Neural circuit dynamics is known as spatiotemporally varying activity patterns of synaptically-wired neurons that become active or silent. The investigation of neural circuit dynamics is essential for ...