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Found 11 papers, 3 papers with code
UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentation
Ultrasound is widely used in clinical practice due to its affordability, portability, and safety.
Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models
Providing explainable molecular property predictions is critical for many scientific domains, such as drug discovery and material science.
Masked Video Modeling with Correlation-aware Contrastive Learning for Breast Cancer Diagnosis in Ultrasound
Breast cancer is one of the leading causes of cancer deaths in women.
Multi-Attribute Attention Network for Interpretable Diagnosis of Thyroid Nodules in Ultrasound Images
To overcome this, we propose a novel deep learning framework called multi-attribute attention network (MAA-Net) that is designed to mimic the clinical diagnosis process.
Weakly-supervised High-fidelity Ultrasound Video Synthesis with Feature Decoupling
First, leveraging the advantages of self- and fully-supervised learning, our proposed system is trained in weakly-supervised manner for keypoint detection.
HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images
The hybrid framework consists of a pre-trained backbone and several searched cells (i. e., network building blocks), which takes advantage of the strengths of both NAS and the expert knowledge from existing convolutional neural networks.
The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21
This paper describes the Volctrans' submission to the WMT21 news translation shared task for German->English translation.
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound
In this study, we build a novel multi-label learning (MLL) scheme to identify multiple standard planes and corresponding anatomical structures of fetus simultaneously.
Learning Language Specific Sub-network for Multilingual Machine Translation
These jointly trained models often suffer from performance degradation on rich-resource language pairs.
The Volctrans Machine Translation System for WMT20
This paper describes our VolcTrans system on WMT20 shared news translation task.
Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information
We investigate the following question for machine translation (MT): can we develop a single universal MT model to serve as the common seed and obtain derivative and improved models on arbitrary language pairs?
Ranked #3 on
Machine Translation
on WMT2014 English-French
(using extra training data)
