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.
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
Passive acoustic monitoring (PAM) has become a powerful tool for studying wildlife by continuously recording environmental soundscapes. However, analysing large acoustic datasets remains highly time-consuming, as recordings are often annotated manually by domain experts. In Read more