Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks ...

Loft Orbital's YAM-9 satellite now runs AI in orbit, classifying imagery and returning plain-English insights instead of raw data dumps.

Abstract: In One-Class Classification (OCC) problems, the classifier is trained with samples of a class considered normal, such that exceptional patterns can be identified as anomalies. Indeed, for ...

The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification. The dataset consists of 5-second-long ...

Near-infrared (NIR) spectroscopy is a promising tool for optimizing seed analyses quickly and assertively. The aim of this study was to investigate the viability of NIR in association with chemometric ...

RFF can be applicable to many other machine learning algorithms than the above. The author will provide implementations of the other algorithms soon. This module supports training/inference on GPU.

Abstract: Hyperspectral image classification has been a very active area of research in recent years. It faces challenges related with the high dimensionality of the data and the limited availability ...

In response to the problem of inadequate utilization of local information in PolSAR image classification using Vision Transformer in existing studies, this paper proposes a Vision Transformer method ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

Land cover mapping is of great interest in the Alps region for monitoring the surface occupation changes (e.g. forestation, urbanization, etc). In this pilot study, we investigate how time series of ...