This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as ...

Recently, text-based image generation models can automatically create high-resolution, high-quality images solely from ...

In this paper, we propose a new idea of LEArning Decomposition (LEAD), which decouples features into source-known and -unknown components to identify target-private data. Technically, LEAD initially ...

A number of agencies are enthusiastically working to develop tools that involve artificial intelligence and machine learning. The Department of Veterans ... which can be employed with broad data sets.

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For ...

Superhydrides are materials that can store significantly more hydrogen than conventional hydrides and present a highly promising option for applications such as hydrogen storage and ...

SAVANA uses machine learning to accurately identify structural variants—large genomic alterations such as insertions, deletions, duplications, or rearrangements—and the resulting copy number ...

Image Recognition as a Service is a scalable #AWS-powered web app that exposes a deep learning model via REST API, using EC2 auto-scaling and load balancing to handle image input and return ...

Abstract: Benefited from image-text contrastive learning ... features more robust and informative for multi-label recognition. For better PEFT, we further combine both prompt tuning and adapter ...

In recent years, in-air writing gesture recognition using radars has gained substantial ... to form a drawing pattern that serves as an input to a ShuffleNet-based deep learning model. Data from 14 ...