Search Results for author: Zhanghexuan Ji

Found 8 papers, 3 papers with code

A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning

no code implementations5 May 2022 Yan Shen, Zhanghexuan Ji, Chunwei Ma, Mingchen Gao

Based on our particle filter inference algorithm, a semi-supervised learn-ing algorithm is utilized for learning tracking network on intermittent labeled frames by variational inference.

Variational Inference Visual Object Tracking

FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation

1 code implementation16 Oct 2021 Yan Shen, Jian Du, Han Zhao, Benyu Zhang, Zhanghexuan Ji, Mingchen Gao

Federated adversary domain adaptation is a unique distributed minimax training task due to the prevalence of label imbalance among clients, with each client only seeing a subset of the classes of labels required to train a global model.

Domain Adaptation

LAViTeR: Learning Aligned Visual and Textual Representations Assisted by Image and Caption Generation

no code implementations4 Sep 2021 Mohammad Abuzar Shaikh, Zhanghexuan Ji, Dana Moukheiber, Yan Shen, Sargur Srihari, Mingchen Gao

Pre-training visual and textual representations from large-scale image-text pairs is becoming a standard approach for many downstream vision-language tasks.

Image Captioning Image Generation +2

Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment

1 code implementation4 Sep 2021 Zhanghexuan Ji, Mohammad Abuzar Shaikh, Dana Moukheiber, Sargur Srihari, Yifan Peng, Mingchen Gao

Self-supervised learning provides an opportunity to explore unlabeled chest X-rays and their associated free-text reports accumulated in clinical routine without manual supervision.

Representation Learning Self-Supervised Learning

An End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation

no code implementations1 Sep 2021 Yan Shen, Zhanghexuan Ji, Mingchen Gao

Many segmentation tasks for biomedical images can be modeled as the minimization of an energy function and solved by a class of max-flow and min-cut optimization algorithms.

Brain Tumor Segmentation Tumor Segmentation

Scribble-based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation

no code implementations5 Nov 2019 Zhanghexuan Ji, Yan Shen, Chunwei Ma, Mingchen Gao

In this paper, we use only two kinds of weak labels, i. e., scribbles on whole tumor and healthy brain tissue, and global labels for the presence of each substructure, to train a deep learning model to segment all the sub-regions.

Brain Tumor Segmentation Tumor Segmentation +1

Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data

1 code implementation20 Sep 2019 Chunwei Ma, Zhanghexuan Ji, Mingchen Gao

Three-dimensional medical image segmentation is one of the most important problems in medical image analysis and plays a key role in downstream diagnosis and treatment.

Ensemble Learning Heart Segmentation +3

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