Kun Yan

About Kun Yan

Kun Yan, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at Peking University, specializes in the field of Computer Vision, Natural Language Processing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Deep Learning Model Based on Multisequence MRI Images for Assessing Adverse Pregnancy Outcome in Placenta Accreta

CTSSeg: Consistent Teacher-Student model for magnetic resonance image Segmentation

ECANodule: Accurate Pulmonary Nodule Detection and Segmentation with Efficient Channel Attention

Two-shot video object segmentation

Inferring prototypes for multi-label few-shot image classification with word vector guided attention

Exploring a Universal Training Method for Medical Image Classification

Aligning visual prototypes with bert embeddings for few-shot learning

Few-shot image classification with multi-facet prototypes

Kun Yan Information

University

Position

___

Citations(all)

272

Citations(since 2020)

271

Cited By

62

hIndex(all)

4

hIndex(since 2020)

4

i10Index(all)

3

i10Index(since 2020)

3

Email

University Profile Page

Google Scholar

Kun Yan Skills & Research Interests

Computer Vision

Natural Language Processing

Top articles of Kun Yan

Deep Learning Model Based on Multisequence MRI Images for Assessing Adverse Pregnancy Outcome in Placenta Accreta

Journal of Magnetic Resonance Imaging

2024/2

CTSSeg: Consistent Teacher-Student model for magnetic resonance image Segmentation

2023/7/10

ECANodule: Accurate Pulmonary Nodule Detection and Segmentation with Efficient Channel Attention

2023/6/18

Two-shot video object segmentation

2023

Inferring prototypes for multi-label few-shot image classification with word vector guided attention

Proceedings of the AAAI Conference on Artificial Intelligence

2022/6/28

Exploring a Universal Training Method for Medical Image Classification

2022/5/13

Kun Yan
Kun Yan

H-Index: 1

Ping Wang
Ping Wang

H-Index: 3

Aligning visual prototypes with bert embeddings for few-shot learning

2021/8/24

Few-shot image classification with multi-facet prototypes

2021/6/6

Representative local feature mining for few-shot learning

2021/6/6

See List of Professors in Kun Yan University(Peking University)

Co-Authors

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