Open-Vocabulary Vision Models as Agentic Infrastructure: What Breaks When Grounding Fails
How open-vocabulary detection and segmentation models become grounding infrastructure for AI agents — and where that grounding silently fails.
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Coverage of computer vision and multimodal models — vision transformers, object detection, segmentation, and image and video understanding.
Image Segmentation in Production: From SAM to Real-World Deployment
A practitioner's guide to segmentation model choice and deployment: SAM vs. U-Net/Mask R-CNN, latency, post-processing, domain shift, and evaluation metrics.
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Vision Transformers vs CNNs: Which Architecture Wins, and When
A technical comparison of vision transformers and CNNs — patch embeddings, attention, inductive bias, data efficiency, and when to use each architecture.
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