ACE: Adaptive Confusion Energy for Natural World Data Distribution

Understand

With the development of deep learning, standard classification problems have achieved good results.

• However, conventional classification problems are often too idealistic.
• Most data in the natural world usually have imbalanced distribution and fine-grained characteristics.
• Recently, many state-of-the-art approaches tend to focus on one or another separately, but rarely on both.