Naseeb Singh

640 citations
43 papers · 385 · h-index 12

Impact in

Papers in

Co-authors
V.K. Tewari (11 shared papers)C.M. Pareek (5 shared papers)Dev Kumar Das (1 shared paper)A. K. Sinha (1 shared paper)Prabir Kumar Biswas (6 shared papers)Simardeep Kaur (15 shared papers)Rakesh Bhardwaj (13 shared papers)Burhan U. Choudhury (4 shared papers)
Journals
Artificial Intelligence in Agriculture (3 papers)Ecological Informatics (2 papers)Journal of Food Composition and Analysis (2 papers)Food Research International (1 paper)Planta (1 paper)
Partner nations
IndiaSwitzerlandUnited States

In The Last Decade

Naseeb Singh

37 papers receiving 368 citations

Peers

Naseeb Singh
Comparison fields: 5 of 82
  • Analytical Chemistry 87
  • Plant Science 165
  • Biophysics 20
  • Control and Systems Engineering 58
  • Animal Science and Zoology 20
Replace Shuhuai Zhang with:
Shuhuai Zhang Japan
Suming Chen Taiwan
Shashikant Sadistap India
John Reidar Mathiassen Norway
Mengmeng Qiao China
Nelson Richard Makange China
P. Chen United States
Junxiong Zhang China
Jiangming Jia China
Naseeb Singh relative to Shuhuai Zhang Japan Shuhuai Zhang's profile →
Citations per field
00.5×2×4×6×7.3×
Shuhuai Zhang · 1×
Citations per year

Countries citing papers authored by Naseeb Singh

Since Specialization
Citations

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

Fields of papers citing papers by Naseeb Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Naseeb Singh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Naseeb Singh Line = papers co-authored together Naseeb Singh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A comparison of Fourier transform and wavelet transform methods for detection and classification of faults on transmission lines
Dev Kumar Das, Naseeb Singh, A. K. Sinha
200654
2
Image processing based real-time variable-rate chemical spraying system for disease control in paddy crop
Artificial Intelligence in Agriculture ·V.K. Tewari, C.M. Pareek, Gurdeep Lal, L. K. Dhruw, Naseeb Singh
202043
3
Image processing algorithms for in-field cotton boll detection in natural lighting conditions
Artificial Intelligence in Agriculture ·Naseeb Singh, V.K. Tewari, Prabir Kumar Biswas, C.M. Pareek, L. K. Dhruw
202125
4
Semantic segmentation of in-field cotton bolls from the sky using deep convolutional neural networks
Smart Agricultural Technology ·Naseeb Singh, V.K. Tewari, Prabir Kumar Biswas, L. K. Dhruw, C.M. Pareek, Himanshu Singh
202221
5
Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
Food Bioscience ·Simardeep Kaur, Naseeb Singh, Preety Dagar, Amit Kumar, Sandeep Jaiswal, Binay Kumar Singh, Rakesh Bhardwaj, Jai Chand Rana, Amritbir Riar
202420
6
Lightweight convolutional neural network models for semantic segmentation of in-field cotton bolls
Artificial Intelligence in Agriculture ·Naseeb Singh, V.K. Tewari, Prabir Kumar Biswas, L. K. Dhruw
202318
7
A comprehensive review on nutritional, nutraceutical, and industrial perspectives of perilla (Perilla frutscens L.) seeds – An orphan oilseed crop
Heliyon ·Simardeep Kaur, Karishma Seem, Ansheef Ali, Sandeep Jaiswal, Praveen Gumachanamardi, Gurkanwal Kaur, Naseeb Singh, Letngam Touthang, Sanjeev Kumar Singh, Rakesh Bhardwaj, Binay Kumar Singh, Vinay Kumar Mishra, Amritbir Riar
202417
8
ProTformer: Transformer-based model for superior prediction of protein content in lablab bean (Lablab purpureus L.) using Near-Infrared Reflectance spectroscopy
Food Research International ·Naseeb Singh, Simardeep Kaur, T. Mithraa, Veerendra Kumar Verma, Amit Kumar, Vinod Choudhary, Rakesh Bhardwaj
202416
9
Optimizing protein content prediction in rice bean (Vigna umbellata L.) by integrating near-infrared reflectance spectroscopy, MPLS, deep learning, and key wavelengths selection algorithms
Journal of Food Composition and Analysis ·Simardeep Kaur, Naseeb Singh, Paras Sharma, R. Ananthan, Mohar Singh, C. Gayacharan, Amit Kumar Singh, Rakesh Bhardwaj
202413
10
Spectral library of crops and discrimination of major vegetables grown in the eastern Himalayan ecosystem: A proximal hyperspectral remote sensing approach
Ecological Informatics ·Burhan U. Choudhury, Rumi Narzari, Md. Zafar, Naseeb Singh, Vinay Kumar Mishra, Mathyam Prabhakar
202313
11
An enhanced chlorophyll estimation model with a canopy structural trait in maize crops: Use of multi-spectral UAV images and machine learning algorithm
Ecological Informatics ·Gaurav Singhal, Burhan U. Choudhury, Naseeb Singh, Jonali Goswami
202412
12
Usability of the Weather Forecast for Tackling Climatic Variability and Its Effect on Maize Crop Yield in Northeastern Hill Region of India
Agronomy ·Debasish Chakraborty, Saurav Saha, Bira Kishore Sethy, Huidrom Dayananda Singh, Naseeb Singh, Romen Sharma, Athokpam Nomita Chanu, Imtisenla Walling, Pashel Rolling Anal, Samik Chowdhury, Samarendra Hazarika, Vinay Kumar Mishra, Prakash Kumar Jha, P. V. Vara Prasad
202211
13
Optimization of irrigation timing for sprinkler irrigation system using convolutional neural network-based mobile application for sustainable agriculture
Smart Agricultural Technology ·Naseeb Singh, Kethavath Ajaykumar, L. K. Dhruw, Burhan U. Choudhury
202311
14
Classification of Broken Maize Kernels Using Artificial Neural Network-Assisted Image-Processing Approach
Journal of Biosystems Engineering ·C.M. Pareek, Naseeb Singh, V.K. Tewari, L. K. Dhruw, Himanshu Singh
202211
15
Near infrared reflectance spectroscopy-driven chemometric modeling for predicting key quality traits in lablab bean (Lablab purpureus L.) Germplasm
Applied Food Research ·Simardeep Kaur, Naseeb Singh, Ernieca Lyngdoh Nongbri, T Mithra, Veerendra Kumar Verma, Amit Kumar, Tanay Joshi, Jai Chand Rana, Rakesh Bhardwaj, Amritbir Riar
202410
16
NIRS-based prediction modeling for nutritional traits in Perilla germplasm from NEH Region of India: comparative chemometric analysis using mPLS and deep learning
Journal of Food Measurement & Characterization ·Simardeep Kaur, Naseeb Singh, Maharishi Tomar, Amit Kumar, Samarth Godara, Siddhant Ranjan Padhi, Jai Chand Rana, Rakesh Bhardwaj, Binay Kumar Singh, Amritbir Riar
20249
17
Finger millet (Eleusine coracana L.): from staple to superfood—a comprehensive review on nutritional, bioactive, industrial, and climate resilience potential
Planta ·Simardeep Kaur, Arti Kumari, Karishma Seem, Gurkanwal Kaur, Deepesh Kumar, Surbhi Verma, Naseeb Singh, Amit Kumar, Manish Kumar, Sandeep Jaiswal, Rakesh Bhardwaj, Binay Kumar Singh, Amritbir Riar
20248
18
Integrating NIR spectroscopy with machine learning and heuristic algorithm-assisted wavelength selection algorithms for protein content prediction in rice bean (Vigna umbellata L.)
Food and Humanity ·Naseeb Singh, Simardeep Kaur, W. S. Philanim, Amit Kumar, Paras Sharma, (unknown), Rakesh Bhardwaj
20248
19
Comparative analysis of deep learning and machine learning-based models for simultaneous prediction of minerals in perilla (Perilla frutescens L.) seeds using near-infrared reflectance spectroscopy
Journal of Food Composition and Analysis ·Naseeb Singh, Simardeep Kaur, Antil Jain, Amit Kumar, Rakesh Bhardwaj, Renu Pandey, Amritbir Riar
20247
20
In-field performance evaluation of robotic arm developed for harvesting cotton bolls
Computers and Electronics in Agriculture ·Naseeb Singh, V.K. Tewari, Prabir Kumar Biswas, L. K. Dhruw, Smrutilipi Hota, Vijay Mahore
20247

About Naseeb Singh

Naseeb Singh is a scholar working on Plant Science, Analytical Chemistry, Mechanical Engineering, Surgery and Civil and Structural Engineering, having authored 43 papers that have together received 385 indexed citations. Recurring topics across this work include Smart Agriculture and AI (18 papers), Spectroscopy and Chemometric Analyses (9 papers), Natural Products and Biological Research (5 papers), Industrial Vision Systems and Defect Detection (4 papers), Spectroscopy Techniques in Biomedical and Chemical Research (4 papers), Agricultural Engineering and Mechanization (4 papers), GABA and Rice Research (3 papers) and Remote Sensing in Agriculture (3 papers). The work is most often cited by research in Analytical Chemistry (87 citations), Plant Science (165 citations), Biophysics (20 citations), Control and Systems Engineering (58 citations) and Animal Science and Zoology (20 citations). Naseeb Singh has collaborated with scholars based in India, Switzerland and United States. Frequent co-authors include V.K. Tewari, C.M. Pareek, Dev Kumar Das, A. K. Sinha, Prabir Kumar Biswas, Simardeep Kaur, Rakesh Bhardwaj, Burhan U. Choudhury, Amritbir Riar and Amit Kumar. Their work appears in journals such as Artificial Intelligence in Agriculture, Ecological Informatics, Journal of Food Composition and Analysis, Food Research International and Planta.

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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