Zero-shot anomaly detection (ZSAD) is a vital problem in computer vision, particularly in real-world scenarios where labeled anomalies are scarce or unavailable. Traditional vision-language models ...
Traditional Optical Character Recognition (OCR) systems are primarily designed to extract plain text from scanned documents or images. While useful, such systems often ignore semantic structure, ...
Object detection has traditionally been a closed-set problem: you train on a fixed list of classes and cannot recognize new ones. Grounding DINO breaks this mold, becoming an open-set, ...
In computing, Graphics Processing Units (GPUs) have transcended their original role, rendering simple polygons to become the workhorses behind realistic gaming worlds, machine learning advancements, ...
Medical imaging is pivotal in modern healthcare, enabling diagnosis, treatment planning, and disease monitoring across modalities like MRI, CT, and pathology slides. However, developing robust AI ...
As Machine Learning and AI technologies continue to advance, the need for efficient and secure methods to store, share, and deploy trained models becomes increasingly critical. Model weights file ...
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