Philippe Mulhem

915 citations
128 papers · 668 · h-index 12

Impact in

Papers in

Philippe Mulhem

118 papers receiving 607 citations

Peers

Philippe Mulhem
Comparison fields: 5 of 57
  • Computer Vision and Pattern Recognition 452
  • Signal Processing 90
  • Artificial Intelligence 207
  • Information Systems 111
  • Media Technology 36
Replace Jean–Pierre Chevallet with:
Jean–Pierre Chevallet France
Sumit Negi India
Ruoyu Zhao China
Jinfeng Zhuang Singapore
Stefan Pletschacher United Kingdom
Ashok C. Popat United States
Biye Jiang China
Zhenxiao Luo China
Mandis Beigi United States
Utz Westermann Austria
Philippe Mulhem relative to Jean–Pierre Chevallet France Jean–Pierre Chevallet's profile →
Citations per field
00.5×2×4×6×7.2×
Jean–Pierre Chevallet · 1×
Citations per year

Countries citing papers authored by Philippe Mulhem

Since Specialization
Citations

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

Fields of papers citing papers by Philippe Mulhem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philippe Mulhem. 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 Philippe Mulhem. The network helps show where Philippe Mulhem may publish in the future.

Co-authors

The 25 scholars most cited alongside Philippe Mulhem, 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 Philippe Mulhem Line = papers co-authored together Philippe Mulhem links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 128 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200383
2 200335
3
Fuzzy Conceptual Graphs for Matching Images of Natural Scenes
200123
4 201820
5 200317
6 200216
7
CLIPS at TREC 11: Experiments in Video Retrieval.
200216
8 201716
9 200914
10 201613
11 200613
12 201012
13 202312
14 199612
15 200411
16 200311
17 200210
18 20059
19
An Improved Method for Image Retrieval using Speech Annotation
20039
20 20239

About Philippe Mulhem

Philippe Mulhem is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Signal Processing and Management Science and Operations Research, having authored 128 papers that have together received 668 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (66 papers), Advanced Image and Video Retrieval Techniques (66 papers), Video Analysis and Summarization (40 papers), Multimodal Machine Learning Applications (19 papers), Topic Modeling (17 papers), Information Retrieval and Search Behavior (12 papers), Web Data Mining and Analysis (11 papers) and Advanced Text Analysis Techniques (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (452 citations), Signal Processing (90 citations), Artificial Intelligence (207 citations), Information Systems (111 citations) and Media Technology (36 citations). Philippe Mulhem has collaborated with scholars based in France, Singapore and United Kingdom. Frequent co-authors include Joo‐Hwee Lim, Qi Chuan Tian, Yves Chiaramella, Mohan Kankanhalli, Georges Quénot, Lorraine Goeuriot, Tele Tan, Haseeb Hassan, Jean Martinet and Mohammed Belkhatir. Their work appears in journals such as Multimedia Tools and Applications, Lecture notes in computer science, Information Retrieval, IEEE Multimedia and Information Processing & Management.

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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