Munan Ning

1.7k citations
29 papers · 1k · 1 hit paper · h-index 13

Impact in

Papers in

Munan Ning

26 papers receiving 1k citations

Munan Ning's Hit Papers

Video-LLaVA: Learning United Visual Representation by Alignment Before Projection 2024 · 192 citations
1920+1Years since publication50100150

Peers

Munan Ning
Comparison fields: 5 of 68
  • Computer Vision and Pattern Recognition 619
  • Artificial Intelligence 274
  • Health Informatics 16
  • Radiology, Nuclear Medicine and Imaging 115
  • Media Technology 19
Replace Qingji Guan with:
Qingji Guan China
Emanuel Ben-Baruch China
Asaf Noy China
Tal Ridnik China
Yutong Bai United States
Ryo Takahashi Japan
Jie-Neng Chen China
Zhongying Deng China
Silvia Cascianelli Italy
Munan Ning relative to Qingji Guan China Qingji Guan's profile →
Citations per field
00.5×2×3.1×
Qingji Guan · 1×
Citations per year

Countries citing papers authored by Munan Ning

Since Specialization
Citations

This map shows the geographic impact of Munan Ning's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Munan Ning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Munan Ning more than expected).

Fields of papers citing papers by Munan Ning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Munan Ning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Munan Ning. The network helps show where Munan Ning may publish in the future.

Co-authors

The 25 scholars most cited alongside Munan Ning, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Munan Ning Line = papers co-authored together Munan Ning links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020256
2
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
Hit paper breakdown →
2024192
3 2021106
4 202286
5 202285
6 202146
7 201842
8 202337
9 202020
10 202219
11 202216
12 202414
13 202514
14 202211
15 202010
16 202010
17 20239
18 20249
19 20269
20 20218

About Munan Ning

Munan Ning is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Waste Management and Disposal and Environmental Chemistry, having authored 29 papers that have together received 1k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Retinal Imaging and Analysis (5 papers), Medical Image Segmentation Techniques (5 papers), Video Surveillance and Tracking Methods (3 papers), Advanced Memory and Neural Computing (2 papers), Marine and coastal ecosystems (1 paper) and Soil erosion and sediment transport (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (619 citations), Artificial Intelligence (274 citations), Health Informatics (16 citations), Radiology, Nuclear Medicine and Imaging (115 citations) and Media Technology (19 citations). Munan Ning has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yang Guo, Yaohua Wang, Yefeng Zheng, Kai Ma, Yang Ye, Yuan Li, Yuexiang Li, Nanjun He, Donghuan Lu and Cheng Bian. Their work appears in journals such as IEEE Transactions on Medical Imaging, Lecture notes in computer science, Image and Vision Computing, ISPRS Journal of Photogrammetry and Remote Sensing and Journal of Visual Communication and Image Representation.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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