Moshe Kam

3.5k citations
187 papers · 2.1k indexed · h-index 22

Impact in

Papers in

Moshe Kam

176 papers receiving 2.0k citations

Peers

Moshe Kam
Comparison fields: 5 of 135
  • Computer Networks and Communications 683
  • Signal Processing 258
  • Artificial Intelligence 671
  • Computer Vision and Pattern Recognition 391
  • Control and Systems Engineering 388
Replace Wei‐Min Shen with:
Wei‐Min Shen United States
Huanlai Xing China
Bo Li China
Xiaofei Xu China
Chun Tung Chou Australia
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Anthony R. Cassandra United States
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Wee Sun Lee Singapore
Alan Fern United States
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Citations per field
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Citations per year

Countries citing papers authored by Moshe Kam

Since Specialization
Citations

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

Fields of papers citing papers by Moshe Kam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20235
2 20221
3 202211
4
Distributed decision fusion using the Neyman-Pearson criterion
20144
5
Evidence combination for hard and soft sensor data fusion
201112
6 20103
7 20084
8 20076
9 200715
10
DEVELOPMENT OF THE INDEPENDENT-TYPE STEER-BY-WIRE SYSTEM USING HILS
20063
11
Network Awareness and the Philadelphia Area Urban Wireless Network Testbed
20053
12 20041
13
Secure Mobile Agents on Ad Hoc Wireless Networks
200318
14 20031
15 20021
16 1997164
17
Convergence and Pattern-Stabilization in the Boltzmann Machine
19882
18 19879
19
ON STABLE POINTS AND CYCLES IN BINARY NEURAL NETWORKS.
19872
20 19850

About Moshe Kam

Moshe Kam is a scholar working on Computer Networks and Communications, Artificial Intelligence, Signal Processing, Statistics, Probability and Uncertainty and Architecture, having authored 187 papers that have together received 2.1k indexed citations. Recurring topics across this work include Distributed Sensor Networks and Detection Algorithms (30 papers), Target Tracking and Data Fusion in Sensor Networks (28 papers), Mobile Ad Hoc Networks (15 papers), Neural Networks and Applications (13 papers), Fault Detection and Control Systems (12 papers), Robotic Path Planning Algorithms (11 papers), Advanced Statistical Process Monitoring (10 papers) and Antenna Design and Analysis (9 papers). The work is most often cited by research in Computer Networks and Communications (683 citations), Signal Processing (258 citations), Artificial Intelligence (671 citations), Computer Vision and Pattern Recognition (391 citations) and Control and Systems Engineering (388 citations). Moshe Kam has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include P. Kalata, W. Steven Gray, Pramod Abichandani, A. Guez, Krishna Chintalapudi, Rachel Greenstadt, Richard Conn, Steven Weber, Lex Fridman and Spiros Mancoridis. Their work appears in journals such as Journal of Forensic Sciences, IEEE Transactions on Antennas and Propagation, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), Pattern Recognition and IEEE Transactions on Power Systems.

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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