IEEE

Meta-Transformers: A Hybrid Approach for Medical Image Segmentation With U-Net and Meta-Learning

Abstract: The increasing demand for accurate and efficient medical image segmentation has driven the development of advanced Artificial Intelligence (AI) models to assist in diagnosing and planning ...
GitHub

coffeegrind123/gemini-for-claude-code

This server acts as a bridge, enabling you to use Claude Code with Google's powerful Gemini models. It translates API requests and responses between the Anthropic format (used by Claude Code) and the ...
IEEE

Zig-RiR: Zigzag RWKV-in-RWKV for Efficient Medical Image Segmentation

Abstract: Medical image segmentation has made significant strides with the development of basic models. Specifically, models that combine CNNs with transformers can successfully extract both local and ...
GitHub

Segmentation fault on shutdown when using Python backend metrics

When shutting down the Triton Inference Server with Python backend while using Triton metrics, a segmentation fault occurs in python_backend process. This happens because Metric::Clear attempts to ...