191 citations · 246 across the 5 of their papers we have counts for
6 papers
Rethinking Continual Learning for Autonomous Agents and Robots
German I. Parisi, Christopher Kanan
Continual learning refers to the ability of a biological or artificial system to seamlessly learn from continuous streams of information while preventing catastrophic forgetting, i…
Challenges and Prospects in Vision and Language Research
Kushal Kafle, Robik Shrestha, Christopher Kanan
Language grounded image understanding tasks have often been proposed as a method for evaluating progress in artificial intelligence. Ideally, these tasks should test a plethora of…
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…
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…