Chen-Ping Yu

891 total citations
16 papers, 303 citations indexed

About

Chen-Ping Yu is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Chen-Ping Yu has authored 16 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 10 papers in Cognitive Neuroscience and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Chen-Ping Yu's work include Visual Attention and Saliency Detection (8 papers), Visual perception and processing mechanisms (7 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Chen-Ping Yu is often cited by papers focused on Visual Attention and Saliency Detection (8 papers), Visual perception and processing mechanisms (7 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Chen-Ping Yu collaborates with scholars based in United States and Brazil. Chen-Ping Yu's co-authors include Talia Konkle, Bria Long, Dimitris Samaras, Gregory J. Zelinsky, Alexandre X. Falcão, Yanxi Liu, Guilherme Ruppert, G. J. Zelinsky, Tomás F. Yago Vicente and Yongming Han and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Psychological Science and Vision Research.

In The Last Decade

Chen-Ping Yu

14 papers receiving 295 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Chen-Ping Yu United States	8	172	151	33	29	26	16	303
Luca Ambrogioni Netherlands	8	264 1.5×	79 0.5×	25 0.8×	41 1.4×	16 0.6×	24	387
Moona Mazher United Kingdom	10	71 0.4×	67 0.4×	36 1.1×	61 2.1×	26 1.0×	31	257
David J. Jilk United States	7	177 1.0×	41 0.3×	21 0.6×	90 3.1×	30 1.2×	11	321
Songyun Xie China	10	163 0.9×	74 0.5×	27 0.8×	25 0.9×	5 0.2×	43	326
L. Sharan United States	4	112 0.7×	207 1.4×	39 1.2×	29 1.0×	42 1.6×	10	347
Kshitij Dwivedi Germany	7	157 0.9×	88 0.6×	12 0.4×	63 2.2×	15 0.6×	16	269
Matthias Kümmerer Germany	8	204 1.2×	373 2.5×	26 0.8×	41 1.4×	19 0.7×	13	451
Steve Grogorick Germany	9	146 0.8×	193 1.3×	16 0.5×	6 0.2×	23 0.9×	22	348
Jonathan Robinson Australia	7	169 1.0×	49 0.3×	38 1.2×	13 0.4×	13 0.5×	14	240
Sebastian Bitzer Germany	9	169 1.0×	17 0.1×	24 0.7×	37 1.3×	25 1.0×	15	271

Countries citing papers authored by Chen-Ping Yu

Since Specialization

Citations

This map shows the geographic impact of Chen-Ping Yu'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 Chen-Ping Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chen-Ping Yu more than expected).

Fields of papers citing papers by Chen-Ping Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chen-Ping Yu. 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 Chen-Ping Yu. The network helps show where Chen-Ping Yu may publish in the future.

Co-authorship network of co-authors of Chen-Ping Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Chen-Ping Yu. A scholar is included among the top collaborators of Chen-Ping Yu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chen-Ping Yu. Chen-Ping Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

Yu, Chen-Ping, et al.. (2019). Modelling attention control using a convolutional neural network designed after the ventral visual pathway. Visual Cognition. 27(5-8). 416–434. 4 indexed citations

Long, Bria, Chen-Ping Yu, & Talia Konkle. (2018). Mid-level visual features underlie the high-level categorical organization of the ventral stream. Proceedings of the National Academy of Sciences. 115(38). E9015–E9024. 140 indexed citations

Yu, Chen-Ping & Talia Konkle. (2017). Map-CNN: A Convolutional Neural Network with Map-like Organizations. Journal of Vision. 17(10). 809–809. 1 indexed citations

Yu, Chen-Ping, et al.. (2016). Searching for Category-Consistent Features. Psychological Science. 27(6). 870–884. 27 indexed citations

Yu, Chen-Ping, et al.. (2016). Generating the features for category representation using a deep convolutional neural network. Journal of Vision. 16(12). 251–251. 2 indexed citations

Yu, Chen-Ping, et al.. (2016). Adding Shape to Saliency: A Proto-object Saliency Map for Predicting Fixations during Scene Viewing. Journal of Vision. 16(12). 1309–1309.

Zelinsky, Gregory J. & Chen-Ping Yu. (2015). Clutter perception is invariant to image size. Vision Research. 116(Pt B). 142–151. 5 indexed citations

Yu, Chen-Ping, Hieu Lê, Gregory J. Zelinsky, & Dimitris Samaras. (2015). Efficient Video Segmentation Using Parametric Graph Partitioning. 3155–3163. 14 indexed citations

Yu, Chen-Ping, Dimitris Samaras, & Gregory J. Zelinsky. (2014). Modeling Visual Clutter Perception using Proto-Object Segmentation. Journal of Vision. 14(10). 365–365. 2 indexed citations

10.

Yu, Chen-Ping, Guilherme Ruppert, Robert H. Collins, et al.. (2014). 3D blob based brain tumor detection and segmentation in MR images. 1192–1197. 17 indexed citations

11.

Yu, Chen-Ping, Dimitris Samaras, & G. J. Zelinsky. (2014). Modeling visual clutter perception using proto-object segmentation. Journal of Vision. 14(7). 4–4. 21 indexed citations

12.

Yu, Chen-Ping, et al.. (2013). Modeling Clutter Perception using Parametric Proto-object Partitioning. Neural Information Processing Systems. 26. 118–126. 2 indexed citations

13.

Vicente, Tomás F. Yago, Chen-Ping Yu, & Dimitris Samaras. (2013). Single Image Shadow Detection Using Multiple Cues in a Supermodular MRF. 126.1–126.11. 18 indexed citations

14.

Geng, Zhiqiang, Yongming Han, & Chen-Ping Yu. (2012). Energy Efficiency Evaluation of Ethylene Product System Based on Density Clustering Data Envelopment Analysis Model. Advanced Science Letters. 9(1). 735–741. 12 indexed citations

15.

Ruppert, Guilherme, et al.. (2011). A new symmetry-based method for mid-sagittal plane extraction in neuroimages. 285–288. 38 indexed citations

16.

Yu, Chen-Ping, et al.. (2007). Modeling the Receptive Field Organization Of Optic Flow Selective MST Neurons.

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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