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20162026
most citedMeasuring Catastrophic Forgetting in Neural Networks

191 citations · 502 across the 31 of their papers we have counts for

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Showing 2017 · cs.CVShow all

5 papers · 2 filters

cs.CV2017★ 23 cited

Aerial Spectral Super-Resolution using Conditional Adversarial Networks

Aneesh Rangnekar, Nilay Mokashi, Emmett Ientilucci +2

Inferring spectral signatures from ground based natural images has acquired a lot of interest in applied deep learning. In contrast to the spectra of ground based images, aerial sp…

cs.CV2017

Convolutional Drift Networks for Video Classification

Dillon Graham, Seyed Hamed Fatemi Langroudi, Christopher Kanan +1

Analyzing spatio-temporal data like video is a challenging task that requires processing visual and temporal information effectively. Convolutional Neural Networks have shown promi…

cs.CV2017★ 21 cited

High-Resolution Multispectral Dataset for Semantic Segmentation

Ronald Kemker, Carl Salvaggio, Christopher Kanan

Unmanned aircraft have decreased the cost required to collect remote sensing imagery, which has enabled researchers to collect high-spatial resolution data from multiple sensor mod…

cs.CV2017

An Analysis of Visual Question Answering Algorithms

Kushal Kafle, Christopher Kanan

In visual question answering (VQA), an algorithm must answer text-based questions about images. While multiple datasets for VQA have been created since late 2014, they all have fla…

cs.CV2017

Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning

Ronald Kemker, Carl Salvaggio, Christopher Kanan

Deep convolutional neural networks (DCNNs) have been used to achieve state-of-the-art performance on many computer vision tasks (e.g., object recognition, object detection, semanti…