no code implementations • 13 Mar 2024 • Ming Dong, Kang Xue, Bolong Zheng, Tingting He
However, there are few methods that consider the impact of data samples on parameter selecting, such as Fish Mask based method.
no code implementations • 13 Mar 2024 • Ming Dong, Yujing Chen, Miao Zhang, Hao Sun, Tingting He
We found that by introducing a small number of specific Chinese rich semantic structures, LLMs achieve better performance than the BERT-based model on few-shot CSC task.
no code implementations • 28 Dec 2023 • Kaiyue Zhou, Ming Dong, Peiyuan Zhi, Shengjin Wang
Numerous point-cloud understanding techniques focus on whole entities and have succeeded in obtaining satisfactory results and limited sparsity tolerance.
no code implementations • 6 Jun 2023 • Qisheng He, Nicholas Summerfield, Ming Dong, Carri Glide-Hurst
Medical image segmentation of tumors and organs at risk is a time-consuming yet critical process in the clinic that utilizes multi-modality imaging (e. g, different acquisitions, data types, and sequences) to increase segmentation precision.
no code implementations • 5 Jun 2023 • Soumyanil Banerjee, Ming Dong, Carri Glide-Hurst
U-shaped networks and its variants have demonstrated exceptional results for medical image segmentation.
1 code implementation • 31 Oct 2022 • Soumyanil Banerjee, Ming Dong, Weisong Shi
COVID-19 has become a matter of serious concern over the last few years.
1 code implementation • 26 Feb 2022 • Jaydeb Sarker, Asif Kamal Turzo, Ming Dong, Amiangshu Bosu
ToxiCR includes a choice to select one of the ten supervised learning algorithms, an option to select text vectorization techniques, eight preprocessing steps, and a large-scale labeled dataset of 19, 571 code review comments.
no code implementations • 1 Nov 2021 • Qisheng He, Weisong Shi, Ming Dong
As a deep learning model typically contains millions of trainable weights, there has been a growing demand for a more efficient network structure with reduced storage space and improved run-time efficiency.
1 code implementation • 25 Jun 2021 • Kaiyue Zhou, Ming Dong, Suzan Arslanturk
Recent supervised point cloud upsampling methods are restricted by the size of training data and are limited in terms of covering all object shapes.
no code implementations • 14 May 2021 • Hajar Emami, Ming Dong, Siamak Nejad-Davarani, Carri Glide-Hurst
In medical image synthesis, model training could be challenging due to the inconsistencies between images of different modalities even with the same patient, typically caused by internal status/tissue changes as different modalities are usually obtained at a different time.
no code implementations • 31 Dec 2020 • Hajar Emami, Qiong Liu, Ming Dong
While Positron emission tomography (PET) imaging has been widely used in diagnosis of number of diseases, it has costly acquisition process which involves radiation exposure to patients.
no code implementations • 24 Dec 2020 • Ling Zhou, Qirong Mao, Ming Dong
Specifically, we propose two new strategies in our AU detection module for more effective AU feature learning: the attention mechanism and the balanced detection loss function.
no code implementations • 22 Dec 2020 • Ming Dong
Traditional long-term planning studies that most utility companies perform based on discrete power levels such as peak or average values cannot reflect system dynamics and often fail to accurately predict system reliability deficiencies.
no code implementations • 27 Jun 2020 • Hajar Emami, Ming Dong, Carri K. Glide-Hurst
Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown rapidly in radiation therapy.
no code implementations • 19 Aug 2019 • Hajar Emami, Majid Moradi Aliabadi, Ming Dong, Ratna Babu Chinnam
Image-to-image translation is to learn a mapping between images from a source domain and images from a target domain.
Generative Adversarial Network Image-to-Image Translation +2
no code implementations • 18 Jul 2019 • Ming Dong, Jian Shi, QingXin Shi
It was compared with traditional methods and our previous sequence prediction method.
no code implementations • 5 May 2019 • Ming Dong, Jessie Sun, Carl Wang
Today, insulated overhead conductors are increasingly used in many places of the world due to the higher operational reliability, elimination of phase-to-phase contact, closer distances between phases and stronger protection for animals.
no code implementations • 6 Jan 2019 • Ming Dong
To solve this important problem, this paper proposes a novel and comprehensive data-driven approach based on asset condition data: K-means clustering as an unsupervised learning method is used to analyze the inner structure of historical asset condition data and produce the asset conditional ages; logistic regression as a supervised learning method takes in both asset physical ages and conditional ages to classify and predict asset statuses.
no code implementations • 9 Dec 2018 • Ming Dong, L. S. Grumbach
The goal of this task is to forecast the annual load of distribution feeders.
no code implementations • CVPR 2018 • Shixing Chen, Caojin Zhang, Ming Dong
In transfer learning, one seeks to transfer related information from source tasks with sufficient data to help with the learning of target task with only limited data.
no code implementations • 2 May 2018 • Ming Dong, Benzhe Li, Alex Nassif
Residential transformer population is a critical type of asset that many electric utility companies have been attempting to manage proactively and effectively to reduce unexpected failures and life losses that are often caused by transformer overloading.
no code implementations • ICCV 2017 • Haotian Xu, Ming Dong, Zichun Zhong
Previous approaches on 3D shape segmentation mostly rely on heuristic processing and hand-tuned geometric descriptors.
no code implementations • CVPR 2017 • Shixing Chen, Caojin Zhang, Ming Dong, Jialiang Le, Mike Rao
Human age is considered an important biometric trait for human identification or search.