World's Best Scientists 2026 revealed!
Sensors
H-index 114

Sensors

1424-8220

Published by: MDPI

https://www.mdpi.com/journal/sensors

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Engineering and Technology 36 852 1777 63

Additional Metrics

Number of Best Scientists*: 5885
Documents by Best Scientists*: 9669
Top 100 Ranked Scientists*: 119
SCIMAGO H-index: 273
SCIMAGO SJR: 0.764
Impact Factor: 3.5

Overview

Top Research Topics at Sensors?

Sensors generally zeroes in on subjects such as Artificial intelligence, Computer vision, Real-time computing, Algorithm and Wireless sensor network. It holds forums on Artificial intelligence that merges themes from other disciplines such as Machine learning and Pattern recognition. The journal encompasses Wireless sensor network studies in the context of Computer network as a whole.

  • Artificial intelligence (18.38%)
  • Computer vision (8.30%)
  • Real-time computing (6.29%)

What are the most cited papers published in the journal?

  • Metal oxide gas sensors: Sensitivity and influencing factors (1582 citations)
  • Accuracy and Resolution of Kinect Depth Data for Indoor Mapping Applications (1299 citations)
  • Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition (1183 citations)

Research areas of the most cited articles at Sensors:

The published papers investigate areas of study like Artificial intelligence, Nanotechnology, Wireless sensor network, Computer vision and Biosensor. The journal papers focus on Artificial intelligence but the discussions also offer insight into other areas such as Machine learning and Pattern recognition. The published papers deal with Wireless sensor network in conjunction with Real-time computing and similar fields in Simulation.

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Sensors (based on the number of publications) are:

  • Kang Ryoung Park (68 papers) published 2 papers at the last edition, 4 less than at the previous edition,
  • Yong He (43 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • René Kizek (40 papers) absent at the last edition,
  • Vojtech Adam (40 papers) absent at the last edition,
  • Ralf Moos (38 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Sensors (based on the number of publications) are:

  • Chinese Academy of Sciences (1095 papers) published 158 papers at the last edition, 65 less than at the previous edition,
  • Beihang University (487 papers) published 43 papers at the last edition, 37 less than at the previous edition,
  • Wuhan University (450 papers) published 37 papers at the last edition, 37 less than at the previous edition,
  • Tsinghua University (416 papers) published 29 papers at the last edition, 14 less than at the previous edition,
  • Zhejiang University (393 papers) published 40 papers at the last edition, 30 less than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 8.07% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 8.25% were posted by at least one author from the top 10 institutions publishing in the journal. Another 4.05% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 11.02% of all publications and 76.67% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • Machine Learning in Agriculture: A Comprehensive Updated Review.

    Lefteris Benos;Aristotelis C. Tagarakis;Georgios Dolias;Remigio Berruto

    (2021)
    715 Citations
  • Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review.

    Hugo F. Posada-Quintero;Ki H. Chon

    (2020)
    447 Citations
  • A Review of Piezoelectric PVDF Film by Electrospinning and Its Applications

    Gulnur Kalimuldina;Nursultan Turdakyn;Ingkar Abay;Alisher Medeubayev

    (2020)
    381 Citations
  • The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise.

    Andrea Nicolò;Carlo Massaroni;Emiliano Schena;Massimo Sacchetti

    (2020)
    377 Citations
  • Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network

    Naresh K. Trivedi;Vinay Gautam;Abhineet Anand;Hani Moaiteq Aljahdali

    (2021)
    361 Citations
  • A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

    Ziqi Huang;Yang Shen;Jiayi Li;Marcel Fey

    (2021)
    342 Citations
  • Crack Detection and Comparison Study Based on Faster R-CNN and Mask R-CNN

    Unknown

    (2022)
    311 Citations
  • A Review of RFID Sensors, the New Frontier of Internet of Things.

    Filippo Costa;Simone Genovesi;Michele Borgese;Andrea Michel

    (2021)
    270 Citations
  • Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques.

    Moajjem Hossain Chowdhury;Nazmul Islam Shuzan;Muhammad Enamul Hoque Chowdhury;Zaid Bin Mahbub

    (2020)
    175 Citations
  • Multiclass Skin Lesion Classification Using Hybrid Deep Features Selection and Extreme Learning Machine

    (2022)
    171 Citations

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Best Scientists Contributing to This Journal