Search Results for author:
Found 8 papers, 5 papers with code
Personalizing Federated Instrument Segmentation with Visual Trait Priors in Robotic Surgery
To preserve the unique appearance representation of each site and gradually leverage the inter-site difference, APE introduces appearance regulation and provides customized layer-wise aggregation solutions via hypernetworks for each site's personalized parameters.
Think Step by Step: Chain-of-Gesture Prompting for Error Detection in Robotic Surgical Videos
Our method encapsulates the reasoning processes inherent to surgical activities enabling it to outperform the state-of-the-art by 4. 6% in F1 score, 4. 6% in Accuracy, and 5. 9% in Jaccard index while processing each frame in 6. 69 milliseconds on average, demonstrating the great potential of our approach in enhancing the safety and efficacy of RMIS procedures and surgical education.
SEDMamba: Enhancing Selective State Space Modelling with Bottleneck Mechanism and Fine-to-Coarse Temporal Fusion for Efficient Error Detection in Robot-Assisted Surgery
SEDMamba enhances selective SSM with a bottleneck mechanism and fine-to-coarse temporal fusion (FCTF) to detect and temporally localize surgical errors in long videos.
Deep Learning Based Automatic Modulation Recognition: Models, Datasets, and Challenges
Automatic modulation recognition (AMR) detects the modulation scheme of the received signals for further signal processing without needing prior information, and provides the essential function when such information is missing.
An Efficient Deep Learning Model for Automatic Modulation Recognition Based on Parameter Estimation and Transformation
Automatic modulation recognition (AMR) is a promising technology for intelligent communication receivers to detect signal modulation schemes.
OH-Former: Omni-Relational High-Order Transformer for Person Re-Identification
Transformers have shown preferable performance on many vision tasks.
Remote Sensing Change Detection Based on Multidirectional Adaptive Feature Fusion and Perceptual Similarity
In this paper we propose a novel multidirectional fusion and perception network for change detection in bi-temporal very-high-resolution remote sensing images.
Change Detection
Change detection for remote sensing images
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A Spatiotemporal Multi-Channel Learning Framework for Automatic Modulation Recognition
Automatic modulation recognition (AMR) plays a vital role in modern communication systems.
