David Rivas-Lalaleo

493 citations
32 papers · 159 indexed · h-index 8
Topics
Greenhouse Technology and Climate Control (4 papers)Energy Efficient Wireless Sensor Networks (3 papers)Plant and soil sciences (2 papers)
Journals
SHILAP Revista de lepidopterologíaAnnals of Internal MedicineSensors
Partner nations
EcuadorSpainVenezuela

In The Last Decade

David Rivas-Lalaleo

25 papers receiving 151 citations

Peers

David Rivas-Lalaleo
Comparison fields: 5 of 64
  • Plant Science 53
  • Electrical and Electronic Engineering 30
  • Computer Networks and Communications 29
  • Control and Systems Engineering 18
  • Computer Vision and Pattern Recognition 14
Replace Muhammad Khurram with:
Muhammad Khurram Pakistan
Anuradha Jayakody Sri Lanka
Fatchul Arifin Indonesia
Vedant Khandelwal United States
Abbas H. Miry Iraq
Imanol Picallo Spain
M. Rajmohan India
P A Harsha Vardhini India
Temitope Mapayi South Africa
S. Muruganandam India
David Rivas-Lalaleo relative to Muhammad Khurram Pakistan Muhammad Khurram's profile →
Citations per field
00.5×1.5×
Muhammad Khurram · 1×
Citations per year

Countries citing papers authored by David Rivas-Lalaleo

Since Specialization
Citations

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

Fields of papers citing papers by David Rivas-Lalaleo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Rivas-Lalaleo. 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 David Rivas-Lalaleo. The network helps show where David Rivas-Lalaleo may publish in the future.

Co-authorship network of co-authors of David Rivas-Lalaleo

This figure shows the co-authorship network connecting the top 25 collaborators of David Rivas-Lalaleo. A scholar is included among the top collaborators of David Rivas-Lalaleo 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 David Rivas-Lalaleo. David Rivas-Lalaleo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Object Detection and Comparison of Different Shapes and Materials using Kinect
0
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About David Rivas-Lalaleo

David Rivas-Lalaleo is a scholar working on Health Information Management, Human-Computer Interaction and General Social Sciences, having authored 32 papers that have together received 159 indexed citations. Recurring topics across this work include Greenhouse Technology and Climate Control (4 papers), Energy Efficient Wireless Sensor Networks (3 papers) and Plant and soil sciences (2 papers). The work is most often cited by research in Human-Computer Interaction (12 citations), Computer Science Applications (8 citations) and Plant Science (53 citations). David Rivas-Lalaleo has collaborated with scholars based in Ecuador, Spain and Venezuela. Frequent co-authors include Mónica Huerta, José Luis Rojo‐Álvarez, Sergio Muñoz-Romero, Jacqueline Llanos, Víctor H. Andaluz, Ricardo Mendoza-González, Washington X. Quevedo, Emilio Hernández⋆, Juan José Sánchez Muñoz and Joaquín Vaquero. Their work appears in journals such as SHILAP Revista de lepidopterología, Annals of Internal Medicine and Sensors.

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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