For example, Fine-tuning deep CNN models on specific MS COCO categories (PDF). It covers our freely available software py-faster-rcnn-ft which allows straightforward fine tuning of deep convolutional neural networks for image classification.
Machine learning models are powerful, yet they often sideline the domain experts who understand the data best. In conventional active learning pipelines, the model drives the process while the user simply responds, leaving domain knowledge Read more
Passive Acoustic Monitoring (PAM) enables continuous and non-invasive biodiversity monitoring, but analysing large acoustic datasets remains difficult because sound event detectors usually require temporally precise annotations. Creating such instance-level labels is expensive and requires expert Read more
Visual-Language-Action (VLA) models are typically trained through imitation learning, which teaches policies to reproduce demonstrated actions but provides limited supervision about the conditions that define task success. We propose a framework that automatically extracts executable Read more