Edgar Scavino

1.3k citations
27 papers · 651 indexed · h-index 12
Topics
Vehicle License Plate Recognition (5 papers)Image and Object Detection Techniques (4 papers)Industrial Vision Systems and Defect Detection (4 papers)

In The Last Decade

Edgar Scavino

26 papers receiving 633 citations

Peers

Edgar Scavino
Comparison fields: 5 of 83
  • Industrial and Manufacturing Engineering 234
  • Industrial and Manufacturing Engineering 199
  • Building and Construction 118
  • Automotive Engineering 85
  • Computer Vision and Pattern Recognition 74
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Citations per field
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Citations per year

Countries citing papers authored by Edgar Scavino

Since Specialization
Citations

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

Fields of papers citing papers by Edgar Scavino

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edgar Scavino

This figure shows the co-authorship network connecting the top 25 collaborators of Edgar Scavino. A scholar is included among the top collaborators of Edgar Scavino 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 Edgar Scavino. Edgar Scavino 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
#WorkIndexed citations
1 1
2 7
3 23
4 6
5 188
6 133
7 7
8 8
9
DNA computation algorithm for recyclable waste paper sorting.
1
10 24
11 3
12
Chromaticity based waste paper grade identification
5
13 7
14 23
15
Waste Paper Grade Identification System using Window Features
11
16
An efficient paper grade identification method for automatic recyclable waste paper sorting
13
17 29
18 9
19 19
20 19

About Edgar Scavino

Edgar Scavino is a scholar working on Industrial and Manufacturing Engineering, Media Technology and Industrial and Manufacturing Engineering, having authored 27 papers that have together received 651 indexed citations. Recurring topics across this work include Vehicle License Plate Recognition (5 papers), Image and Object Detection Techniques (4 papers) and Industrial Vision Systems and Defect Detection (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (234 citations), Industrial and Manufacturing Engineering (199 citations) and Building and Construction (118 citations). Edgar Scavino has collaborated with scholars based in Malaysia, Bangladesh and Pakistan. Frequent co-authors include M. A. Hannan, Mahmuda Akhtar, Rawshan Ara Begum, Aini Hussain, Hassan Basri, Hidayah Basri, Mohd Marzuki Mustafa, Dzuraidah Abd Wahab, Ahmed A. Hussain and Hasan Basri. Their work appears in journals such as Expert Systems with Applications, Waste Management and Applied Soft Computing.

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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