Search Results for author: Jialei Chen

Found 9 papers, 0 papers with code

Generalizable Semantic Vision Query Generation for Zero-shot Panoptic and Semantic Segmentation

no code implementations21 Feb 2024 Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Hiroshi Murase

However, one of the gaps in synthesizing pseudo vision queries, ie, vision queries for unseen categories, is describing fine-grained visual details through semantic embeddings.

Open Vocabulary Semantic Segmentation Panoptic Segmentation

CLIP Is Also a Good Teacher: A New Learning Framework for Inductive Zero-shot Semantic Segmentation

no code implementations3 Oct 2023 Jialei Chen, Daisuke Deguchi, Chenkai Zhang, Xu Zheng, Hiroshi Murase

Moreover, to enhance the ability to discriminate unseen categories, PLM consisting of pseudo labels and weight generation is designed.

Segmentation Semantic Segmentation +1

Deep Generative Imputation Model for Missing Not At Random Data

no code implementations16 Aug 2023 Jialei Chen, Yuanbo Xu, Pengyang Wang, Yongjian Yang

Existing statistical methods model the MNAR mechanism by different decomposition of the joint distribution of the complete data and the missing mask.


Project Florida: Federated Learning Made Easy

no code implementations21 Jul 2023 Daniel Madrigal Diaz, Andre Manoel, Jialei Chen, Nalin Singal, Robert Sim

Federated learning enables model training across devices and silos while the training data remains within its security boundary, by distributing a model snapshot to a client running inside the boundary, running client code to update the model, and then aggregating updated snapshots across many clients in a central orchestrator.

Federated Learning Management

Federated Multilingual Models for Medical Transcript Analysis

no code implementations4 Nov 2022 Andre Manoel, Mirian Hipolito Garcia, Tal Baumel, Shize Su, Jialei Chen, Dan Miller, Danny Karmon, Robert Sim, Dimitrios Dimitriadis

Federated Learning (FL) is a novel machine learning approach that allows the model trainer to access more data samples, by training the model across multiple decentralized data sources, while data access constraints are in place.

Federated Learning

Uncertainty-Aware Deep Co-training for Semi-supervised Medical Image Segmentation

no code implementations23 Nov 2021 Xu Zheng, Chong Fu, Haoyu Xie, Jialei Chen, Xingwei Wang, Chiu-Wing Sham

However, due to the scarcity of labeled data, the features extracted by the models are limited in supervised learning, and the quality of predictions for unlabeled data also cannot be guaranteed.

Image Segmentation Semantic Segmentation +1

APIK: Active Physics-Informed Kriging Model with Partial Differential Equations

no code implementations22 Dec 2020 Jialei Chen, Zhehui Chen, Chuck Zhang, C. F. Jeff Wu

We present in this work a PDE Informed Kriging model (PIK), which introduces PDE information via a set of PDE points and conducts posterior prediction similar to the standard kriging method.

Active Image Synthesis for Efficient Labeling

no code implementations5 Feb 2019 Jialei Chen, Yujia Xie, Kan Wang, Chuck Zhang, Mani A. Vannan, Ben Wang, Zhen Qian

The great success achieved by deep neural networks attracts increasing attention from the manufacturing and healthcare communities.

Image Generation Small Data Image Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.