Abstract: Human-labeled training datasets are essential for convolutional neural networks (ConvNets) in satellite image scene classification. Annotation errors are unavoidable due to the complexity of ...

This standalone MATLAB project generates edge groups from images, converts manual polyline annotations into edge-group labels, and trains RF and PCA/SVM classifiers. The repository includes the ...

Abstract: In real-life scenarios, the field-of-view angles captured by cameras are typically constrained. This has led to a growing demand for panoramic images to cater to various applications, such ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...

This tutorial implements the Multiple Signal Classification (MUSIC) Algorithm [1] on the AI Engine. MUSIC is a popular algorithm for Direction of Arrival (DOA) estimation in antenna array systems.

Last month, a local TikToker posted a photo of a Denver Art Museum label, with this text: “Saw my first AI-generated museum label at the Denver Art Museum” accompanied by screaming audio. The label, ...

Elon Musk’s X is the latest social network to roll out a feature to label edited images as “manipulated media,” if a post by Elon Musk is to be believed. But the company has not clarified how it will ...

In keeping with years of recommendations from universities and education advocates that teachers be involved in the development of ed-tech tools, the interactive learning platform Wooclap recently ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

A team of Monash University researchers have successfully piloted an algorithm to identify incorrect penicillin allergy labels and educate patients presenting to community pharmacies. Patients are ...

A new technical paper titled “Scanning electron microscopy-based automatic defect inspection for semiconductor manufacturing: a systematic review” was published by researchers at KU Leuven and imec.