Bimodal SegNet: Instance Segmentation Fusing Events and RGB Frames for Robotic Grasping

A recent study evaluated the effectiveness of deep learning models and large language models (LLMs) for vulnerability detection, focusing on models like ReVeal and LineVul across four datasets: Juliet, Devign, BigVul, and ICVul. The research highlights the gap between benchmark performance and real-world applicability, emphasizing the need for systematic evaluation in practical scenarios.

A novel Deep Learning pipeline has been introduced for establishing feature correspondences in endoscopic image pairs, addressing the challenges of accurate spatial understanding in minimally invasive surgical procedures. This approach focuses on self-supervised contrastive embedding adaptation to enhance image matching capabilities in complex anatomical environments.