Youssef Es-Saady

1.0k total citations · 1 hit paper
32 papers, 558 citations indexed

About

Youssef Es-Saady is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Plant Science. According to data from OpenAlex, Youssef Es-Saady has authored 32 papers receiving a total of 558 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 8 papers in Plant Science. Recurrent topics in Youssef Es-Saady's work include Smart Agriculture and AI (8 papers), Spectroscopy and Chemometric Analyses (7 papers) and Handwritten Text Recognition Techniques (6 papers). Youssef Es-Saady is often cited by papers focused on Smart Agriculture and AI (8 papers), Spectroscopy and Chemometric Analyses (7 papers) and Handwritten Text Recognition Techniques (6 papers). Youssef Es-Saady collaborates with scholars based in Morocco, France and Canada. Youssef Es-Saady's co-authors include Mohamed El Hajji, Driss Mammass, Adel Hafiane, Raphaël Canals, Hassan Douzi, Mustapha Amrouch, Mohamed Baslam, Mohamed El Ansari and Rachid Bouharroud and has published in prestigious journals such as Remote Sensing, Computers and Electronics in Agriculture and Multimedia Tools and Applications.

In The Last Decade

Youssef Es-Saady

31 papers receiving 520 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research

2021 159 citations Adel Hafiane, Youssef Es-Saady et al. profile →

Peers

Youssef Es-Saady

PS

AI

CSA

AC

CVPR

Venkatramaphanikumar Sistla India

Bogdan Orza Romania

Lukas Lukas Indonesia

Sameerchand Pudaruth Mauritius

Yousef Atoum United States

Darlis Herumurti Indonesia

Mohamad Nizam Bin Ayub Malaysia

Andi Wahju Rahardjo Emanuel Indonesia

Vijay S. Rajpurohit India

Habib Khan South Korea

Venkatramaphanikumar Sistla India

Youssef Es-Saady

181 ×0.8

PS

122 ×0.8

AI

13 ×0.1

CSA

60 ×0.6

AC

74 ×0.9

CVPR

Citations per year, relative to Youssef Es-Saady Youssef Es-Saady (= 1×) peers Venkatramaphanikumar Sistla

Countries citing papers authored by Youssef Es-Saady

Since Specialization

Citations

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

Fields of papers citing papers by Youssef Es-Saady

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Youssef Es-Saady. 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 Youssef Es-Saady. The network helps show where Youssef Es-Saady may publish in the future.

Co-authorship network of co-authors of Youssef Es-Saady

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

All Works

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20 of 20 papers shown

1.

Hajji, Mohamed El, et al.. (2025). An Architecture for Intelligent Tutoring in Virtual Reality: Integrating LLMs and Multimodal Interaction for Immersive Learning. Information. 16(7). 556–556. 2 indexed citations

2.

Hajji, Mohamed El, et al.. (2024). A hybrid approach for early-identification of at-risk dropout students using LSTM-DNN networks. Education and Information Technologies. 29(14). 18839–18857. 2 indexed citations

3.

Es-Saady, Youssef, et al.. (2024). BERTopic for Enhanced Idea Management and Topic Generation in Brainstorming Sessions. Information. 15(6). 365–365. 11 indexed citations

4.

Es-Saady, Youssef, et al.. (2024). Enhancing DeepLabV3+ for aerial image semantic segmentation using weighted upsampling. SPIRE - Sciences Po Institutional REpository. 1–6. 1 indexed citations

5.

Hajji, Mohamed El, et al.. (2024). Optimization of agrifood supply chains using Hyperledger Fabric blockchain technology. Computers and Electronics in Agriculture. 227. 109503–109503. 2 indexed citations

6.

Hajji, Mohamed El, et al.. (2023). Video-Based Learning Recommender Systems: A Systematic Literature Review. IEEE Transactions on Learning Technologies. 17. 485–497. 4 indexed citations

7.

Hajji, Mohamed El, et al.. (2023). The Power of Personalization: A Systematic Review of Personality-Adaptive Chatbots. SN Computer Science. 4(5). 29 indexed citations

8.

Hafiane, Adel, et al.. (2023). CactiViT: Image-based smartphone application and transformer network for diagnosis of cactus cochineal. Artificial Intelligence in Agriculture. 9. 12–21. 6 indexed citations

9.

Hajji, Mohamed El, et al.. (2023). The impact of educational chatbot on student learning experience. Education and Information Technologies. 29(8). 10153–10176. 83 indexed citations

10.

Es-Saady, Youssef, et al.. (2022). Meteorological Data and UAV Images for the Detection and Identification of Grapevine Disease Using Deep Learning. SPIRE - Sciences Po Institutional REpository. 1–4. 5 indexed citations

11.

Hajji, Mohamed El, et al.. (2021). Predicting learner’s performance through video sequences viewing behavior analysis using educational data-mining. Education and Information Technologies. 26(5). 5799–5814. 29 indexed citations

12.

Es-Saady, Youssef, et al.. (2019). Handwritten Tifinagh Characters Recognition Using Deep Convolutional Neural Networks. Sensing and Imaging. 20(1). 13 indexed citations

13.

Es-Saady, Youssef, et al.. (2018). Deep Neural Networks for Otolith Identification. 18(3). 99–110. 2 indexed citations

14.

Es-Saady, Youssef, et al.. (2016). Automatic recognition of plant leaves diseases based on serial combination of two SVM classifiers. 561–566. 66 indexed citations

15.

Es-Saady, Youssef, et al.. (2016). A new otolith recognition system based on image contour analysis. Journal of Entomology and Zoology Studies. 4(1). 580–590. 1 indexed citations

16.

Es-Saady, Youssef, et al.. (2016). Automatic Recognition of the Damages and Symptoms on Plant Leaves Using Parallel Combination of Two Classifiers. 11 indexed citations

17.

Es-Saady, Youssef, et al.. (2014). Amazigh Characters Automatic Recognition: Overview and Prospects. 2 indexed citations

18.

Es-Saady, Youssef, et al.. (2014). Handwritten Tifinagh Character Recognition Using Baselines Detection Features. 7 indexed citations

19.

Amrouch, Mustapha, et al.. (2012). A Novel Feature Set for Recognition of Printed Amazigh Text using Maximum Deviation and HMM. International Journal of Computer Applications. 44(12). 23–30. 6 indexed citations

20.

Amrouch, Mustapha, et al.. (2009). Printed amazigh character recognition by a hybrid approach based on Hidden Markov Models and the Hough transform. 2. 356–360. 12 indexed citations

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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