mlsanityData to 14 Oct 2026

Deep Fast Vision: A Python Library for Accelerated Deep Transfer Learning Vision Prototyping

arXiv 2311.06169 ↗First posted 10 Nov 2023cs.CV cs.LG eess.IVcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 19 references that are in the map. First posted on arXiv 10 Nov 2023.

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References · 5

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,611
  3. 2019A Comprehensive Survey on Transfer Learningcited by 1,160
  4. 2015Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)cited by 1,070
  5. 2023Improving Performance in Colorectal Cancer Histology Decomposition using Deep and Ensemble Machine Learningcited by 7

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