As deep learning models scale, they become increasingly competitive from domains
spanning from computer vision to natural language processing; however, this happens at …

Multilabel representation learning is recognized as a challenging problem that can be
associated with either label dependencies between object categories or data-related issues …

The convolutional neural network (CNN) has achieved great success in fulfilling computer
vision tasks despite large computation overhead against efficient deployment. Channel …

Explaining the generalization characteristics of deep learning is an emerging topic in
advanced machine learning. There are several unanswered questions about how learning …

Coral reefs are among the most biologically diverse and economically valuable ecosystems
on Earth, but they are threatened by climate change. Understanding how reefs developed …

As the world takes cognizance of AI's growing role in greenhouse gas (GHG) and carbon
emissions, the focus of AI research & development is shifting towards inclusion of energy …

Recent algorithmic developments, specifically in deep learning, have propelled computer
vision forward for practical applications. However, the high computational complexity and …

The field of computer vision is rapidly evolving, particularly in the context of new methods of
neural architecture design. These models contribute to (1) the Climate Crisis-increased CO2 …

Climate change continues to be a pressing issue that currently affects society at-large. It is
important that we as a society, including the Computer Vision (CV) community take steps to …