Abstract: Graph convolution networks (GCNs) have achieved impressive results for few-shot hyperspectral image (HSI) classification. However, current methods focus on migrating labels from support ...

Here’s something fun. Our hacker [Willow Cunningham] has sent us a copy of their homework. This is their final project for the “ECE 574: Cluster Computing” course at the University of Maine, Orono. It ...

A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...

Convolution is used in a variety of signal-processing applications, including time-domain-waveform filtering. In a recent series on the inverse fast Fourier transform (FFT), we concluded with a ...

Event-based cameras are bio-inspired vision sensors that mimic the sparse and asynchronous activation of the animal retina, offering advantages such as low latency and low computational load in ...

School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 610031 Sichuan, China Artificial Intelligence Research Institute, Southwest Jiaotong University, Chengdu 610031 ...

Abstract: Cracks are among the most common, most likely, and earliest of all pavement distresses. Detecting and repairing cracks as early as possible can help extend the service life of pavements.

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This project involves implementing the forward pass of an 18-layer Convolutional Neural Network (CNN) in MATLAB for object detection. The goal is to classify 32x32x3 images into one of ten categories, ...