568 citations · 2.2k across the 54 of their papers we have counts for
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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…
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…
FearNet: Brain-Inspired Model for Incremental Learning
Ronald Kemker, Christopher Kanan
Incremental class learning involves sequentially learning classes in bursts of examples from the same class. This violates the assumptions that underlie methods for training standa…
Measuring Catastrophic Forgetting in Neural Networks
Ronald Kemker, Marc McClure, Angelina Abitino +2
Deep neural networks are used in many state-of-the-art systems for machine perception. Once a network is trained to do a specific task, e.g., bird classification, it cannot easily…
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…
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…