Search Results for author:
Found 36 papers, 18 papers with code
Meta-CQG: A Meta-Learning Framework for Complex Question Generation over Knowledge Bases
Complex question generation over knowledge bases (KB) aims to generate natural language questions involving multiple KB relations or functional constraints.
Adapting SAM for Surgical Instrument Tracking and Segmentation in Endoscopic Submucosal Dissection Videos
Specifically, with a tiny subset of frames for segmentation, we ensure accurate segmentation across the entire surgical video.
Selective Temporal Knowledge Graph Reasoning
Temporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently.
Class-Incremental Few-Shot Event Detection
Therefore, this paper proposes a new task, called class-incremental few-shot event detection.
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction
After instruction tuning, KnowCoder further exhibits strong generalization ability on unseen schemas and achieves up to $\textbf{12. 5%}$ and $\textbf{21. 9%}$, compared to sota baselines, under the zero-shot setting and the low resource setting, respectively.
EndoOOD: Uncertainty-aware Out-of-distribution Detection in Capsule Endoscopy Diagnosis
Wireless capsule endoscopy (WCE) is a non-invasive diagnostic procedure that enables visualization of the gastrointestinal (GI) tract.
OSSAR: Towards Open-Set Surgical Activity Recognition in Robot-assisted Surgery
Existing algorithms dedicated to surgical activity recognition predominantly cater to pre-defined closed-set paradigms, ignoring the challenges of real-world open-set scenarios.
Privacy-Preserving Synthetic Continual Semantic Segmentation for Robotic Surgery
The problem becomes worse when it limits releasing the dataset of the old instruments for the old model due to privacy concerns and the unavailability of the data for the new or updated version of the instruments for the continual learning model.
Endo-4DGS: Endoscopic Monocular Scene Reconstruction with 4D Gaussian Splatting
In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes.
Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery
There is clear evidence in the results that zero-shot prediction on pre-trained weights in computer vision datasets or naive fine-tuning is not sufficient to use the foundation model in the surgical domain directly.
SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge
Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to decision support systems.
Retrieval-Augmented Code Generation for Universal Information Extraction
Therefore, in this paper, we propose a universal retrieval-augmented code generation framework based on LLMs, called Code4UIE, for IE tasks.
An In-Context Schema Understanding Method for Knowledge Base Question Answering
The Knowledge Base Question Answering (KBQA) task aims to answer natural language questions based on a given knowledge base.
Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion
Considering that Coupled Dictionary Learning (CDL) method can obtain a reasonable linear mathematical relationship between resource images, we propose a novel CDL-based Synthetic Aperture Radar (SAR) and multispectral pseudo-color fusion method.
Nested Event Extraction upon Pivot Element Recogniton
Since existing NEE datasets (e. g., Genia11) are limited to specific domains and contain a narrow range of event types with nested structures, we systematically categorize nested events in the generic domain and construct a new NEE dataset, called ACE2005-Nest.
ProtoEM: A Prototype-Enhanced Matching Framework for Event Relation Extraction
To comprehensively understand their intrinsic semantics, in this paper, we obtain prototype representations for each type of event relation and propose a Prototype-Enhanced Matching (ProtoEM) framework for the joint extraction of multiple kinds of event relations.
Sample-adaptive Augmentation for Point Cloud Recognition Against Real-world Corruptions
Robust 3D perception under corruption has become an essential task for the realm of 3D vision.
Rethinking Exemplars for Continual Semantic Segmentation in Endoscopy Scenes: Entropy-based Mini-Batch Pseudo-Replay
More seriously, data privacy and storage issues may lead to the unavailability of old data when updating the model.
Semi-supervised Learning for Segmentation of Bleeding Regions in Video Capsule Endoscopy
Notably, we develop the segmentation annotations for this dataset ourselves.
Landmark Detection using Transformer Toward Robot-assisted Nasal Airway Intubation
This paper proposes a transformer-based landmark detection solution with deformable DeTR and the semantic-aligned-matching module for detecting landmarks in robot-assisted intubation.
Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery
We further establish a CL framework on three public surgical datasets in the context of surgical settings that consist of overlapping classes between old and new surgical VQLA tasks.
CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery
Therefore, a surgical Visual Question Localized-Answering (VQLA) system would be helpful for medical students and junior surgeons to learn and understand from recorded surgical videos.
LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion
Given the exuberant development of the denoising diffusion probabilistic model (DDPM) in computer vision, we introduce a WCE LLIE framework based on the multi-scale convolutional neural network (CNN) and reverse diffusion process.
Semantic Structure Enhanced Event Causality Identification
This is a very challenging task, because causal relations are usually expressed by implicit associations between events.
Domain Adaptive Sim-to-Real Segmentation of Oropharyngeal Organs Towards Robot-assisted Intubation
Robotic-assisted tracheal intubation requires the robot to distinguish anatomical features like an experienced physician using deep-learning techniques.
Surgical-VQLA: Transformer with Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery
In this paper, we propose Visual Question Localized-Answering in Robotic Surgery (Surgical-VQLA) to localize the specific surgical area during the answer prediction.
Domain Adaptive Sim-to-Real Segmentation of Oropharyngeal Organs
In this work, we propose a domain adaptive Sim-to-Real framework called IoU-Ranking Blend-ArtFlow (IRB-AF) for image segmentation of oropharyngeal organs.
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
Rich Event Modeling for Script Event Prediction
Fundamentally, it is based on the proposed rich event description, which enriches the existing ones with three kinds of important information, namely, the senses of verbs, extra semantic roles, and types of participants.
Two-stage Contextual Transformer-based Convolutional Neural Network for Airway Extraction from CT Images
In the first stage, the total airway mask and CT images are provided to the subnetwork, and the intrapulmonary airway mask and corresponding CT scans to the subnetwork in the second stage.
HiSMatch: Historical Structure Matching based Temporal Knowledge Graph Reasoning
This is actually a matching task between a query and candidate entities based on their historical structures, which reflect behavioral trends of the entities at different timestamps.
Complex Evolutional Pattern Learning for Temporal Knowledge Graph Reasoning
Furthermore, these models are all trained offline, which cannot well adapt to the changes of evolutional patterns from then on.
What is Event Knowledge Graph: A Survey
Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are also an essential kind of knowledge in the world, which trigger the spring up of event-centric knowledge representation form like Event KG (EKG).
Integrating Deep Event-Level and Script-Level Information for Script Event Prediction
In this paper, we propose a Transformer-based model, called MCPredictor, which integrates deep event-level and script-level information for script event prediction.
The Influence of Age and Gender Information on the Diagnosis of Diabetic Retinopathy: Based on Neural Networks
This paper proposes the importance of age and gender information in the diagnosis of diabetic retinopathy.
