Challenges, tasks, and opportunities in modeling agent-based complex systems

L An, V Grimm, A Sullivan, BL Turner Ii, N Malleson… - Ecological …, 2021 - Elsevier
Humanity is facing many grand challenges at unprecedented rates, nearly everywhere, and
at all levels. Yet virtually all these challenges can be traced back to the decision and …

Comparing deep learning models for low-light natural scene image enhancement and their impact on object detection and classification: Overview, empirical …

R Al Sobbahi, J Tekli - Signal Processing: Image Communication, 2022 - Elsevier
Low-light image (LLI) enhancement is an important image processing task that aims at
improving the illumination of images taken under low-light conditions. Recently, a …

PSD: Principled synthetic-to-real dehazing guided by physical priors

Z Chen, Y Wang, Y Yang, D Liu - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Deep learning-based methods have achieved remarkable performance for image dehazing.
However, previous studies are mostly focused on training models with synthetic hazy …

Learning to resize images for computer vision tasks

H Talebi, P Milanfar - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
For all the ways convolutional neural nets have revolutionized computer vision in recent
years, one important aspect has received surprisingly little attention: the effect of image size …

Advancing image understanding in poor visibility environments: A collective benchmark study

W Yang, Y Yuan, W Ren, J Liu… - … on Image Processing, 2020 - ieeexplore.ieee.org
Existing enhancement methods are empirically expected to help the high-level end
computer vision task: however, that is observed to not always be the case in practice. We …

Single image deraining: A comprehensive benchmark analysis

S Li, IB Araujo, W Ren, Z Wang… - Proceedings of the …, 2019 - openaccess.thecvf.com
We present a comprehensive study and evaluation of existing single image deraining
algorithms, using a new large-scale benchmark consisting of both synthetic and real-world …

Applications, databases and open computer vision research from drone videos and images: a survey

Y Akbari, N Almaadeed, S Al-Maadeed… - Artificial Intelligence …, 2021 - Springer
Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an
emerging application attracting significant attention from researchers in various areas of …

[PDF][PDF] All-in-One Underwater Image Enhancement Using Domain-Adversarial Learning.

PM Uplavikar, Z Wu, Z Wang - CVPR workshops, 2019 - openaccess.thecvf.com
Raw underwater images are degraded due to wavelength dependent light attenuation and
scattering, limiting their applicability in vision systems. Another factor that makes enhancing …

Source-free domain adaptation for real-world image dehazing

H Yu, J Huang, Y Liu, Q Zhu, M Zhou… - Proceedings of the 30th …, 2022 - dl.acm.org
Deep learning-based source dehazing methods trained on synthetic datasets have
achieved remarkable performance but suffer from dramatic performance degradation on real …

Delving into robust object detection from unmanned aerial vehicles: A deep nuisance disentanglement approach

Z Wu, K Suresh, P Narayanan, H Xu… - Proceedings of the …, 2019 - openaccess.thecvf.com
Object detection from images captured by Unmanned Aerial Vehicles (UAVs) is becoming
increasingly useful. Despite the great success of the generic object detection methods …