Abstract: Due to the measurement equipment and human errors, low-quality annotation in real-world industrial datasets is inevitable. Challenges such as sample imbalance, noisy labels and fault mode ...

Tu-Quyen Dao, a senior biochemistry student, is studying how AI can be applied to improve healthcare. Tu-Quyen Dao. Photo credit: Eileen Chong. I understand that you were involved in a research ...

💡 TL;DR: Given an image and nothing else (i.e. no prompts or candidate labels), NOVIC can generate an accurate fine-grained textual classification label in real-time, with coverage of the vast ...

Trained on one of the world’s largest real-world video datasets from Grass and hosted on Inference.net’s scalable AI infrastructure, the model delivers high-accuracy video annotation at a fraction of ...

Abstract: Nucleus instance segmentation from histopathology images suffers from the extremely laborious and expert-dependent annotation of nucleus instances. As a promising solution to this task, ...

AI models require well-labeled data to achieve high accuracy. Without structured datasets, they struggle with precision, bias, and real-world reliability. Data annotation companies lay the foundation ...

I process my annotation using "[digitalsreeni-image-annotator] (https://github.com/bnsreenu/digitalsreeni-image-annotator)" it provide a json file in COCO format ...

Group activity recognition (GAR), which aims to identify activities performed collectively in videos, has gained significant attention recently. Existing GAR datasets typically annotate only a single ...