Sajad Kiani
- Biomedical Engineering top 10%
- Analytical Chemistry top 1%
- Food Science top 10%
- Plant Science
- Molecular Biology
- Co-authors
- Saeid MinaeiMahdi Ghasemi‐VarnamkhastiSaskia M. van RuthAbdolabbas JafariL.W.D. van RaamsdonkHassan YazdanpanahMahdi AyyariJavad Feizy
- Topics
- Spectroscopy and Chemometric Analyses (19 papers)Advanced Chemical Sensor Technologies (11 papers)Smart Agriculture and AI (6 papers)
- Partner nations
- IranNetherlandsItaly
In The Last Decade
Sajad Kiani
27 papers receiving 679 citations
Peers
Comparison fields: 5 of 82
- Biomedical Engineering 324
- Analytical Chemistry 321
- Food Science 141
- Plant Science 141
- Molecular Biology 119
Countries citing papers authored by Sajad Kiani
This map shows the geographic impact of Sajad Kiani'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 Sajad Kiani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sajad Kiani more than expected).
Fields of papers citing papers by Sajad Kiani
This network shows the impact of papers produced by Sajad Kiani. 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 Sajad Kiani. The network helps show where Sajad Kiani may publish in the future.
Co-authorship network of co-authors of Sajad Kiani
This figure shows the co-authorship network connecting the top 25 collaborators of Sajad Kiani. A scholar is included among the top collaborators of Sajad Kiani 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 Sajad Kiani. Sajad Kiani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 10 | |
| 5 | 23 | |
| 6 | 6 | |
| 7 | 11 | |
| 8 | 22 | |
| 9 | 49 | |
| 10 | 50 | |
| 11 | 13 | |
| 12 | Computer vision system coupled with an Artificial Neural Network to rainbow trout eggs quality evaluation. | 2 |
| 13 | 72 | |
| 14 | Discriminating The Corn Plants From The Weeds By Using Artificial Neural Networks | 3 |
| 15 | Crop Detection and Positioning in the Field Using Discriminant Analysis and Neural Networks Based on Shape Features | 27 |
| 16 | 3 | |
| 17 | Application of Co-occurrence Matrix on Wavelet Coefficients for Crop-weed Discrimination | 3 |
| 18 | 2 | |
| 19 | Automatic On-Line Depth Control of Seeding Units Using a Non-Contacting Ultrasonic Sensor | 13 |
| 20 | Effect of Time and Temperature on Moisture Content, Shrinkage, and Rehydration of Dried Onion | 25 |
About Sajad Kiani
Sajad Kiani is a scholar working on Analytical Chemistry, Horticulture and Food Science, having authored 28 papers that have together received 699 indexed citations. Recurring topics across this work include Spectroscopy and Chemometric Analyses (19 papers), Advanced Chemical Sensor Technologies (11 papers) and Smart Agriculture and AI (6 papers). The work is most often cited by research in Analytical Chemistry (321 citations), Food Science (141 citations) and Biomedical Engineering (324 citations). Sajad Kiani has collaborated with scholars based in Iran, Netherlands and Italy. Frequent co-authors include Saeid Minaei, Mahdi Ghasemi‐Varnamkhasti, Saskia M. van Ruth, Abdolabbas Jafari, L.W.D. van Raamsdonk, Hassan Yazdanpanah, Mahdi Ayyari, Javad Feizy, S. Kamgar and Seyed Mahmoud Mousavi. Their work appears in journals such as Scientific Reports, Food Chemistry and Journal of Food Engineering.
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.