Ahmed Kechida

16 papers receiving 639 citations

Hit Papers

Deep learning techniques to classify agricultural crops t...20212026202220242022202150100150

Peers

Ahmed Kechida
Comparison fields: 5 of 79
  • Computer Vision and Pattern Recognition 239
  • Plant Science 203
  • Ecology 136
  • Aerospace Engineering 119
  • Safety, Risk, Reliability and Quality 106
Replace Amine Mohammed Taberkit with:
Amine Mohammed Taberkit Algeria
Abdelmalek Bouguettaya Algeria
Xijian Fan China
Kaixiang Zhang United States
Xubing Yang China
Matthew Coombes United Kingdom
Moataz M. Abdelwahab Egypt
Lixue Zhu China
Pierre-Luc St-Charles Canada
Henry Medeiros United States
Ahmed Kechida relative to Amine Mohammed Taberkit Algeria Amine Mohammed Taberkit's profile →
Citations per field
00.5×
Amine Mohammed Taberkit · 1×
Citations per year

Countries citing papers authored by Ahmed Kechida

Since Specialization
Citations

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

Fields of papers citing papers by Ahmed Kechida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ahmed Kechida

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 0
2 91
3
Deep learning techniques to classify agricultural crops through UAV imagery: a reviewbreakdown →
198
4 3
5 1
6 120
7 12
8
A review on early wildfire detection from unmanned aerial vehicles using deep learning-based computer vision algorithmsbreakdown →
173
9 2
10
A Survey on Lightweight CNN-Based Object Detection Algorithms for Platforms with Limited Computational Resources
9
11 8
12 11
13 14
14 4
15 4
16 11
17 5

About Ahmed Kechida

Ahmed Kechida is a scholar working on Human-Computer Interaction, Analytical Chemistry and Mechanics of Materials, having authored 17 papers that have together received 666 indexed citations. Recurring topics across this work include Ultrasonics and Acoustic Wave Propagation (7 papers), Remote Sensing in Agriculture (4 papers) and Smart Agriculture and AI (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (239 citations), Safety, Risk, Reliability and Quality (106 citations) and Media Technology (52 citations). Ahmed Kechida has collaborated with scholars based in Algeria. Frequent co-authors include Abdelmalek Bouguettaya, Amine Mohammed Taberkit, Hafed Zarzour, Redouane Drai, Abderrezak Guessoum, Malika Boudraa, A. Guessoum, Mohamed Salah Azzaz and Mustapha Benssalah. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Transactions on Neural Networks and Learning Systems and Signal Processing.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026