Aug 25, 2016 · This paper presents an interactive machine learning paradigm with experts in the loop for improving image grouping. We demonstrate that image ...
Image grouping in knowledge-rich domains is challenging, since domain knowledge and human expertise are key to transform image pixels into meaningful content.
[PDF] Intelligent medical image grouping through interactive learning
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This work presents an interactive machine learning paradigm that allows experts to become an integral part of the learning process and effectively improves ...
Abstract: Image grouping in knowledge-rich domains is challenging, since domain knowledge and human expertise are key to transform image pixels into ...
In our paradigm, dermatologists encode their domain knowledge about the medical images by grouping a small subset of images via a carefully designed interface.
In our paradigm, dermatologists encode their domain knowledge about the medical images by grouping a small subset of images via a carefully designed interface.
Jan 22, 2024 · Interactive medical image segmentation using deep learning with image-specific fine tuning. In IEEE Transactions on Medical Imaging 37, 1562 ...
This survey provides a comprehensive insight into DL-based medical image segmentation by covering its application domains, model exploration, analysis of state ...
This comprehensive review delivers an overview of recent advances in medical imaging using deep neural networks.
The interac- tive learning process involves three stages: key- word prediction, caption generation, and model updates. First, the model predicts a list of key-.