Deep learning-based vision is characterized by intricate frameworks that
often necessitate a profound understanding, presenting a barrier to newcomers
and limiting broad adoption. With many researchers grappling with the
constraints of smaller datasets, there's a pronounced reliance on pre-trained
neural networks, especially for tasks such as image classification. This
reliance is further intensified in niche imaging areas where obtaining vast
datasets is challenging. Despite the widespread use of transfer learning as a
remedy to the small dataset dilemma, a conspicuous absence of tailored auto-ML
solutions persists. Addressing these challenges is "Deep Fast Vision", a python
library that streamlines the deep learning process. This tool offers a
user-friendly experience, enabling results through a simple nested dictionary
definition, helping to democratize deep learning for non-experts. Designed for
simplicity and scalability, Deep Fast Vision appears as a bridge, connecting
the complexities of existing deep learning frameworks with the needs of a
diverse user base.

利用 Python 库 Deep Fast Vision 简化深度学习过程，连接现有深度学习框架与广大用户需求，通过简单的嵌套字典定义为非专家提供了易于使用且可量化的体验，解决了小数据集困境和缺乏定制化自动机器学习解决方案的问题。