1 code implementation • 19 Mar 2023 • Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Ronald Kemker, Christopher Kanan
Compared to REMIND and prior arts, SIESTA is far more computationally efficient, enabling continual learning on ImageNet-1K in under 2 hours on a single GPU; moreover, in the augmentation-free setting it matches the performance of the offline learner, a milestone critical to driving adoption of continual learning in real-world applications.
no code implementations • 30 Oct 2019 • Ryne Roady, Tyler L. Hayes, Ronald Kemker, Ayesha Gonzales, Christopher Kanan
We found that input perturbation and temperature scaling yield the best performance on large scale datasets regardless of the feature space regularization strategy.
1 code implementation • 1 Apr 2018 • Ronald Kemker, Utsav B. Gewali, Christopher Kanan
Deep learning continues to push state-of-the-art performance for the semantic segmentation of color (i. e., RGB) imagery; however, the lack of annotated data for many remote sensing sensors (i. e. hyperspectral imagery (HSI)) prevents researchers from taking advantage of this recent success.
1 code implementation • 26 Mar 2018 • Ronald Kemker, Ryan Luu, Christopher Kanan
These low-shot learning frameworks will reduce the manual image annotation burden and improve semantic segmentation performance for remote sensing imagery.
no code implementations • 21 Feb 2018 • German I. Parisi, Ronald Kemker, Jose L. Part, Christopher Kanan, Stefan Wermter
Humans and animals have the ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan.
no code implementations • ICLR 2018 • Ronald Kemker, Christopher Kanan
Arguably, the best method for incremental class learning is iCaRL, but it requires storing training examples for each class, making it challenging to scale.
no code implementations • 7 Aug 2017 • Ronald Kemker, Marc McClure, Angelina Abitino, Tyler Hayes, Christopher Kanan
Deep neural networks are used in many state-of-the-art systems for machine perception.
1 code implementation • 19 Mar 2017 • Ronald Kemker, Carl Salvaggio, Christopher Kanan
In this paper, we adapt state-of-the-art DCNN frameworks in computer vision for semantic segmentation for MSI imagery.
no code implementations • 6 Mar 2017 • 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 modalities more frequently and easily.