Artificial Intelligence applications in Agriculture
Applications Invited
128
Scopus Publications
2889
Scholar Citations
22
Scholar h-index
55
Scholar i10-index
Scopus Publications
DFI-ADR: Fuzzy Logic-Driven Information Retrieval and Machine Learning for Environmental and Crop Prediction to Optimize Farming Decisions , Surabhi Solanki, Seema Verma International Journal of Information Engineering and Electronic Business, 2025 This paper proposes DFI-ADR (Dynamic Fuzzy Information System with Agriculture Decision Retrieval) aimed at improving agricultural decision-making through case-based reasoning and precise information retrieval.This approach uses fuzzy logic and machine learning techniques, such as IndRNN, to compute similarity scores between historical agricultural cases and new queries.This enables dynamic classification of cases as "distinct," "similar," or "highly comparable" based on fuzzy membership values.These values significantly enhance the accuracy of decisions related to agricultural factors like crop yield, soil quality, and irrigation.The methodology outperforms traditional methods in terms of accuracy, recall, and precision, proving highly effective for agricultural analysis and decisionmaking.In experiments with the Agriculture Dataset Karnataka, DFI-ADR achieved an accuracy of 95%, a precision of 100%, and an F1-score of 94.74%, significantly outperforming traditional methods by a margin of 10-15% across these metrics.These values demonstrate its effectiveness for agricultural analysis and decision-making.
A Survey of Techniques for Improving Information Retrieval through Query Expansion , Surabhi Solanki, Seema Verma, Sachin Kumar International Journal of Information Technology and Computer Science, 2025 This paper presents a comprehensive survey of QE techniques in IR. Core techniques, employed data sources, and methodologies used in the process of query expansion are discussed. The output study highlights four main steps concerned with expanding queries: steps related to preprocessing of data sources and term extraction, calculation of weights and ranking of terms, selection of terms, and finally expansion. The most important findings are that only effective text normalization and removal of stopwords provide a real platform for performing QE. The introduction of contextually relevant terms significantly enhanced relevance feedback and thesaurus-based WordNet expansion techniques. They have been shown to significantly improve retrieval effectiveness as has been realized from various experiments conducted over years now. It also uses the manual query expansion techniques and discusses several automated ways in order to improve retrieval effectiveness. This work, by reviewing the related literature and methodologies, gives an overview of how the techniques of query expansion have been evolving with time and achieved better results in IR systems. The survey offers a valuable resource for researchers and practitioners in information retrieval, shedding light on the advancements, challenges, and future directions in query expansion research.
Review of Segmentation Techniques for Weed Detection in Agricultural Crops Akanksha Bodhale, Seema Verma Procedia Computer Science, 2025 This study explores the role of deep learning in identifying and managing weeds in agriculture, a critical challenge for enhancing crop productivity. As the global population grows, increasing food production is essential. Weeds significantly hinder crop growth, making accurate identification vital. Deep learning techniques, which analyze elements like color, form, texture, and spectrum, offer promising solutions for distinguishing between crops and weeds. This review examines various segmentation techniques used in weed identification, comparing their effectiveness and potential for practical application. The findings aim to advance weed management strategies, contributing to improved agricultural productivity and the development of automated systems for precise weed detection.
Review of Segmentation Techniques for Weed Detection in Agricultural Crops Akanksha Bodhale, Seema Verma Procedia Computer Science, 2025 This study explores the role of deep learning in identifying and managing weeds in agriculture, a critical challenge for enhancing crop productivity. As the global population grows, increasing food production is essential. Weeds significantly hinder crop growth, making accurate identification vital. Deep learning techniques, which analyze elements like color, form, texture, and spectrum, offer promising solutions for distinguishing between crops and weeds. This review examines various segmentation techniques used in weed identification, comparing their effectiveness and potential for practical application. The findings aim to advance weed management strategies, contributing to improved agricultural productivity and the development of automated systems for precise weed detection.
Institutional and Technological Barriers to Elearning Adoption in Aviation Maintenance Education: A Comparative Study of India and the Middle East Aashutosh Mishra, Seema Verma, Kamal Jaiswal, Balgopal Singh 2025 12th International Conference on Reliability Infocom Technologies and Optimization Trends and Future Directions Icrito 2025, 2025 The aviation industry is undergoing rapid technological transformation, which necessitates the professional development of aircraft maintenance personnel in alignment with evolving requirements. However, disparities in Aircraft Maintenance Engineering (AME) education highlight the challenges of adopting e-learning within training institutes. This study examines the technological and institutional limitations affecting e-learning implementation in aviation maintenance education, with a focus on India and the Middle East. A mixed-methods design was employed: the quantitative phase utilised a 5 -point Likert scale survey, while the qualitative phase comprised structured interviews. A total of 335 participants, including students, educators, and academic administrators-were selected through stratified purposive sampling. Quantitative data were analysed using statistical tools, and qualitative responses were interpreted through thematic analysis. Findings indicate that technological infrastructure (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{r}=\mathbf{0. 5 6}$</tex>), educators' digital literacy (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{r}=0.48$</tex>), and institutional preparedness (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{r}=\mathbf{0. 4 1}$</tex>) were significant barriers to e-learning adoption. Institutions in the Middle East demonstrated higher readiness (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$M=3.56$</tex>) compared with those in India (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$M=3.18$</tex>), primarily due to superior infrastructure and greater funding. Stakeholders identified faculty training (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$M=4.45$</tex>), advanced learning management systems (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$M=4.32$</tex>), and policy reforms (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{M} \boldsymbol{=} \mathbf{4. 2 8}$</tex>) as key solutions. The study concludes that enhancing AME education requires targeted faculty development, improved infrastructure, and blended learning approaches. Practical and policy-oriented recommendations are provided to enable stakeholders to implement advanced e-learning technologies more effectively.
Enhancing Query Expansion with ML-SSO: A Machine Learning, Semantic, Statistical, and Ontological Framework Surabhi Solanki, Seema Verma, Pulakesh Roy, Sachin Kumar, Rajib Banerjee, Ajay Prasad 2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation Iatmsi 2025, 2025 This paper presents a Machine Learning -Semantic Statistical and Ontological query expansion approach to enhance the performance of information retrieval systems. The proposed methodology ML-SSO looks to combine the strengths of each technique to obtain relevancy and accurately expanded queries. In this, pre-trained word-embed models were used for contextually relevant term expansions, and domain-specific ontologies were used to provide accurate and custom query expansions. Large-scale experiments conducted on benchmark datasets demonstrated that the ML-SSO outperformed traditional ones in MAP, Precision at k (P@10), Recall, and F-measure scores. These results make clear that the ML-SSO query expansion method improves the relevance and accuracy of the Retrieved Document. Future work will be directed towards optimizing the scalability, incorporating dynamic ontology driven into it, and using other advanced models in machine learning to further increase the performance of the system.
A Comprehensive Study of Case-Based Reasoning in Information Retrieval: An Artificial Intelligence Approach Surabhi Solanki, Seema Verma, Prolay Biswas, Pulakesh Roy, Aparna Singh, Surbhi Sharma 2025 International Conference on Pervasive Computational Technologies Icpct 2025, 2025 Information Retrieval (IR) systems which provide accurate and contextually relevant information to healthcare and law etc. where accuracy is very crucial. Traditional information retrieval methods fundamentally based on keyword matching and statistical models usually difficult to achieve the semantic meaning and contextual nuances of queries. Case-Based Reasoning (CBR), as an artificial intelligence technique, provide advance solutions to enhance IR systems based on a set of past cases through adaptive context-supporting retrieval. By taking advantage of past cases data, CBR allows IR systems to interpret complex context-sensitive queries and offer personalized results. The paper provides an overview of traditional IR models, examines the CBR integration into these systems, and evaluates the impact of CBR on retrieval effectiveness and personalization. And finally, we elaborate on the challenges involved with scaling and adapting cases towards real-time retrieval and provide some future directions for research, including integrating machine learning techniques and hybrid models to enhance the relevance, interpretability, and scalability of CBR-based IR systems.
Novel approach for crop weed detection in wheat fields using deep learning algorithms: Machine learning for weed detection Akanksha Bodhale, Seema Verma Fostering Cross Industry Sustainability with Intelligent Technologies, 2024 Agricultural productivity is greatly affected by weeds. To remove these weeds with chemical pesticides is harmful to the ecological environment. Also, with overall level of agricultural production rising, it is becoming more and more crucial to accurately distinguish between crops and weeds in order to perform accurate spraying just on the weeds. For generating precise spraying methods, it is required to identify the crop location and weed location more precisely. In recent years, many weed detection techniques are explored. This approach ranges from conventional to machine learning to deep learning. It is quite necessary to identify the color and texture features from image using image processing techniques for conventional approach. Then these conventional approaches are combined with some classical machine learning techniques. Any classical machine learning method necessitates a limited amount of training time, a low requirement for graphics processing units, and a limited sample size. There are two main approaches to weed detection from images: classification and segmentation.
Satellite Sastri Kota, Giovanni Giambene, Mohammed Abdelsadek, Mohamed-Slim Alouini, Marc Amay, Sarath Babu, Joan Bas, Pietro Cassarà, Sachin Chaudhari, Debabrata Dalai, Tasneem Darwish, Tomaso de Cola, Thomas Delamotte, Ashutosh Dutta, Ayush Dwivedi, Michael Enright, Marco Giordani, Alberto Gotta, Eman Hammad, Tamer Khattab, Andreas Knopp, Gunes Karabulut Kurt, Pablo G. Madoery, B. S. Manoj, Jean-Daniel Medjo Me Biomo, Prashant Pillai, Pramud Rawat, Paresh Saxena, Pat Scanlan, Avinash Sharma, Muhammad Sohaib Solaija, Ray Sperber, Zhili Sun, Daniele Tarchi, Neeraj Varshney, Seema Verma, Simon Watts, Halim Yanikomeroglu, Kanglian Zhao, Liang Zhao Proceedings 2023 IEEE Future Networks World Forum Future Networks Imagining the Network of the Future Fnwf 2023, 2023
Shallow Extension Engineered Dual Metal Surrounding Gate (SEE-DM-SG) MOSFET for Lower Leakages and Submillimeter Wave Applications 12th Indiacom 5th International Conference on Computing for Sustainable Global Development Indiacom 2018, 2018
Evaluation of suitable rice (oryza sativa L.) based cropping system to enhance cropping intensity and profitability in chhattisgarh plain International Journal of Agricultural and Statistical Sciences, 2017
Design of low power Voltage Controlled Oscillator Jyoti Garg, Seema Verma Proceedings on 2012 1st International Conference on Emerging Technology Trends in Electronics Communication and Networking Et2ecn 2012, 2012
Attention-Enhanced VGG-16 Architecture for Precision Weed Detection in Wheat Fields A Bodhale University of Bahrain , 2026 2026
Epstein–barr virus and multiple sclerosis: from pathogenesis and diagnosis to EBV-specific T cell therapy and gene-targeted therapeutics M Pushkarna, A Zwamel, S Verma, H Malathi, M Mustafayeva, H Kaur, ... Journal of Applied Genetics, 1-17 , 2026 2026
Blockchain Forensics for Cryptocurrency-Driven Cybercrime S Verma, P Tripathi, P Arora Cyber Forensic Frameworks for User-Centric Human Threat Intelligence … , 2026 2026
Forensic-Ready Approaches to Insider Threat Mitigation and Human Behavior Analysis P Arora, P Tripathi, S Verma Cyber Forensic Frameworks for User-Centric Human Threat Intelligence … , 2026 2026
Ab initio study of mechanical and functional properties of novel CaZnC and CaZnSi half-Heusler materials PK Kamlesh, UK Gupta, S Verma, M Rani, Y Toual, AS Verma arXiv preprint arXiv:2512.15822 , 2025 2025 Citations: 5
Highly enhanced cyanogen chloride and hydrogen cyanide sensing performance of BC4N monolayer with silicon-doped: A DFT approach MJ Saadh, K Salim, A Kumar, V Jain, S Verma, H Kaur, B Kumari, ... Physica B: Condensed Matter 710, 417248 , 2025 2025 Citations: 1
Nature's Remedies and Conservation: Ethnomedicinal Plants in the Tungnath Region, West Himalaya BS Adhikari, R Kumar, S Verma Oecologia Montana 34 (1), 17-34 , 2025 2025
Impact of whey protein on lipid profiles: A systematic review and meta-analysis IS Gataa, Z Abdullah, MVG Cabrera, S Verma, I Arora, M Monsi, ... Nutrition, Metabolism and Cardiovascular Diseases 35 (6), 103858 , 2025 2025 Citations: 6
Comparative Analysis of Pre-Sowing Seed Treatments on Germination and Growth Metrics of Santalum album L. S Verma, A Sharma, V Chauhan, N Prajapati Proceedings of International Forestry and Environment Symposium 29 , 2025 2025
Enhancing query expansion with ML-SSO: a machine learning, semantic, statistical, and ontological framework S Solanki, S Verma, P Roy, S Kumar, R Banerjee, A Prasad 2025 IEEE International Conference on Interdisciplinary Approaches in … , 2025 2025 Citations: 3
Genetic Parameters and Variability Analysis in Mungbean [Vigna radiata (L.) Wilczek.] A Kumar, M Trivedi, SS Pal, RB Yadav, SK Verma Journal of the Andaman Science Association Vol 30 (1), 39-42 , 2025 2025
Assessment of Genetic Variability and Trait Associations for Yield and Yield Components in Urdbean [Vigna mungo (L.) Hepper] A Kumar, SS Pal, M Trivedi, RB Yadav, SK Verma Journal of the Andaman Science Association Vol 30 (1), 17-22 , 2025 2025
MORPHOLOGICAL AND TAXONOMICAL DESCRIPTIONS OF FIVE SPECIES OF COCCINELLIDAE (LADYBIRD BEETLES)(INSECTA: COLEOPTERA) FROM AGRO-ECOSYSTEM OF HIMACHAL PRADESH SK VERMA INTERNATIONAL JOURNAL OF BIOLOGY 7 (3), 11-14 , 2025 2025
Review of Segmentation Techniques for Weed Detection in Agricultural Crops A Bodhale, S Verma Procedia Computer Science 259, 61-70 , 2025 2025 Citations: 2
The effects of ω− 3 fatty acids on inflammatory and oxidative stress markers in patients with Type 2 diabetes mellitus: A systematic review and meta-analysis of controlled trials K Muzammil, AQ Khaleel, MS Merza, A Kyada, IA Ariffin, S Verma, H Kaur, ... Prostaglandins & Other Lipid Mediators 175, 106887 , 2024 2024 Citations: 11
Weed Spotter: An Advanced Deep Learning Approach for Field Weed Recognition A Bodhale, S Verma Congress on Intelligent Systems, 469-484 , 2024 2024
Emotional Competence and Cognitive Abilities: A Comparative Survey Study of Active and Sedentary College Students. S Choudhary, P Siwach, A Choudhury, S Verma, H Sehrawat Journal of Clinical & Diagnostic Research 18 , 2024 2024 Citations: 1
Estimation of Genetic Parameters for Yield and its Component Traits in Urd Bean [Vigna mungo (L.) Hepper]. MA Sonu, SK Verma, SK Tiwari, SGP Reddy, A Chauhan, S Kumawat, ... Ecology, Environment & Conservation (0971765X) 7 , 2024 2024
Enhanced Image Classification Through Customized Convolutional Spiking Neural Network AK Saini, R Kumar, N Gehlot, S Verma 2024 Parul International Conference on Engineering and Technology (PICET), 1-6 , 2024 2024 Citations: 3
Quantum Computing Research: Ontological Study of the Quantum Computing Research Ecosystem RK Sheoran, S Verma, SK Sheoran, V Yadav Applications and Principles of Quantum Computing, 236-263 , 2024 2024 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Constraints on low-mass, relic dark matter candidates from a surface-operated SuperCDMS single-charge sensitive detector DW Amaral, T Aralis, T Aramaki, IJ Arnquist, E Azadbakht, S Banik, ... Physical Review D 102 (9), 091101 , 2020 2020 Citations: 263
A high-performance network intrusion detection system R Sekar, Y Guang, S Verma, T Shanbhag Proceedings of the 6th ACM Conference on Computer and Communications … , 1999 1999 Citations: 198
A survey on driver behavior detection techniques for intelligent transportation systems R Chhabra, S Verma, CR Krishna 2017 7th International Conference on Cloud Computing, Data Science … , 2017 2017 Citations: 173
Protective effects of few antioxidants on liver function in rats treated with cadmium and mercury. SVS Rana, R Singh, S Verma 1996 Citations: 168
Protective effects of GSH, vitamin E, and selenium on lipid peroxidation in cadmium-fed rats SVS Rana, S Verma Biological Trace Element Research 51 (2), 161-168 , 1996 1996 Citations: 159
Generation and evaluation of artificial mental health records for natural language processing J Ive, N Viani, J Kam, L Yin, S Verma, S Puntis, RN Cardinal, A Roberts, ... NPJ digital medicine 3 (1), 69 , 2020 2020 Citations: 107
Prevalence of menopausal symptoms and its effect on quality of life among rural middle aged women (40–60 years) of Haryana, India M Kalhan, K Singhania, P Choudhary, S Verma, P Kaushal, T Singh International Journal of Applied and Basic Medical Research 10 (3), 183-188 , 2020 2020 Citations: 100
Wearable computing and its application S Jhajharia, SK Pal, S Verma International Journal of Computer Science and Information Technologies 5 (4 … , 2014 2014 Citations: 97
First dark matter search results from Coherent CAPTAIN-Mills AA Aguilar-Arevalo, DSM Alves, S Biedron, J Boissevain, M Borrego, ... Physical Review D 106 (1), 012001 , 2022 2022 Citations: 82
Agile vs waterfall: a comparative analysis V Kannan, S Jhajharia, S Verma International Journal of Science, Engineering and Technology Research … , 2014 2014 Citations: 72
Approaches to sustainable forest management and biodiversity conservation: With pivotal role of non timber forest products MP Shiva, SK Verma 2002 Citations: 69
PAPR reduction of OFDM signals using selective mapping with turbo codes P Sharma, S Verma International Journal of Wireless & Mobile Networks (IJWMN) vol 3 , 2011 2011 Citations: 63
Mercury-induced lipid peroxidation in the liver, kidney, brain and gills of a fresh water fish, Channa punctatus R SVS, R Singh, S Verma Japanese Journal of Ichthyology 42 (3-4), 255-259 , 1995 1995 Citations: 57
Wireless Sensor Network application for water quality monitoring in India S Verma 2012 National conference on computing and communication systems, 1-5 , 2012 2012 Citations: 47
Protective effects of GSH, α-tocopherol, and selenium on lipid-peroxidation in liver and kidney of copper fed rats. SVS Rana, S Verma 1997 Citations: 42
Prospects for detecting axionlike particles at the Coherent CAPTAIN-Mills experiment AA Aguilar-Arevalo, DSM Alves, S Biedron, J Boissevain, M Borrego, ... Physical Review D 107 (9), 095036 , 2023 2023 Citations: 40
First leptophobic dark matter search from the coherent–CAPTAIN-Mills liquid argon detector AA Aguilar-Arevalo, DSM Alves, S Biedron, J Boissevain, M Borrego, ... Physical review letters 129 (2), 021801 , 2022 2022 Citations: 35
Energy aware routing scheme for mobile ad hoc network using variable range transmission P Nayak, R Agarwal, S Verma arXiv preprint arXiv:1209.2550 , 2012 2012 Citations: 34
Energy efficient routing in mobile adhoc networks based on AODV protocol S Verma, P Nayak, R Agarwal International Journal of Computer Science Issues (IJCSI) 9 (6), 344 , 2012 2012 Citations: 26
Challenges in Developing Citizen-Centric E-Governance in Libya. S Verma, S Kumari, M Arteimi, A Deiri, R Kumar Int. Arab. J. e Technol. 2 (3), 152-160 , 2012 2012 Citations: 26
