Search Results for author:
Found 9 papers, 4 papers with code
DeltaNet: Conditional Medical Report Generation for COVID-19 Diagnosis
To reduce the workload of radiologists, we propose DeltaNet to generate medical reports automatically.
PolSAM: Polarimetric Scattering Mechanism Informed Segment Anything Model
PolSAR data presents unique challenges due to its rich and complex characteristics.
Physics-Guided Detector for SAR Airplanes
The main contributions of PGD include the physics-guided self-supervised learning, feature enhancement, and instance perception, denoted as PGSSL, PGFE, and PGIP, respectively.
Ranked #1 on
Object Detection
on SAR-AIRcraft-1.0
(using extra training data)
OCC-MLLM-Alpha:Empowering Multi-modal Large Language Model for the Understanding of Occluded Objects with Self-Supervised Test-Time Learning
There is a gap in the understanding of occluded objects in existing large-scale visual language multi-modal models.
DeltaNet:Conditional Medical Report Generation for COVID-19 Diagnosis
To reduce the workload of radiologists, we propose DeltaNet to generate medical reports automatically.
Universal Segmentation of 33 Anatomies
Firstly, while it is ideal to learn such a model from a large-scale, fully-annotated dataset, it is practically hard to curate such a dataset.
Radiology Report Generation with a Learned Knowledge Base and Multi-modal Alignment
In clinics, a radiology report is crucial for guiding a patient's treatment.
Knowledge Matters: Radiology Report Generation with General and Specific Knowledge
In this paper, we propose a knowledge-enhanced radiology report generation approach introduces two types of medical knowledge: 1) General knowledge, which is input independent and provides the broad knowledge for report generation; 2) Specific knowledge, which is input dependent and provides the fine-grained knowledge for report generation.
CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography
Spine-related diseases have high morbidity and cause a huge burden of social cost.
