Every time a smartphone snaps a photo, millions of tiny light detectors capture the scene and then ferry all that raw data across the chip to a separate processor for storage and number-crunching.

Figures 12-14 are the land use/land cover maps of existing forest reserves in the FCT, namely; Tufa in Abaji, Chihuma, Chikwei, Kusoru and Shaba in Bwari, Maje Abuchi in Gwagwalada, then, Buga Hill, ...

Accurate and reliable segmentation of multiple sclerosis (MS) lesions from magnetic resonance imaging (MRI) is essential for diagnosis and monitoring disease progression. Therefore, a robust and ...

Abstract: The scarcity of labeled samples results in the challenge of small sample size in hyperspectral image (HSI) classification. Transfer learning offers hope for solving this problem. In ...

This repository contains Python notebooks demonstrating image classification using Azure AutoML for Images. These notebooks provide practical examples of building computer vision models for various ...

Abstract: Sample augmentation is crucial for improving land-cover classification performance when the samples are limited. However, the traditional sample augmentation approach concentrates on ...

Looking at the image classification example http://www.deepdetect.com/tutorials/imagenet-classifier/ using googlenet I am not seeing that the mean.binaryproto / mean.npy seems to be used for inference ...