3 papers
cs.CV2026
Class Geometry as Supervision for Sample-Efficient Open-World Detection
Akash Rao, Zhou Chen, Revanth Reddy Palem +3
Open-world object detection requires models to recognize known categories, reject unfamiliar objects, and incorporate new classes over time. This is especially challenging in scarc…
cs.CV2025
FSP-DETR: Few-Shot Prototypical Parasitic Ova Detection
Shubham Trehan, Udhav Ramachandran, Akash Rao +2
Object detection in biomedical settings is fundamentally constrained by the scarcity of labeled data and the frequent emergence of novel or rare categories. We present FSP-DETR, a…
eess.IV2023
ProtoKD: Learning from Extremely Scarce Data for Parasite Ova Recognition
Shubham Trehan, Udhav Ramachandran, Ruth Scimeca +1
Developing reliable computational frameworks for early parasite detection, particularly at the ova (or egg) stage is crucial for advancing healthcare and effectively managing poten…