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vinay kukreja
vinay kukreja
Professor & Director (Research), Chitkara University
Verified email at chitkara.edu.in
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Cited by
Cited by
Year
A novel deep learning model for detection of severity level of the disease in citrus fruits
P Dhiman, V Kukreja, P Manoharan, A Kaur, MM Kamruzzaman, ...
Electronics 11 (3), 495, 2022
4442022
Amalgamated convolutional long term network (CLTN) model for Lemon Citrus Canker Disease Multi-classification
R Sharma, V Kukreja
2022 International conference on decision aid sciences and applications …, 2022
2112022
A Deep Neural Network based disease detection scheme for Citrus fruits
V Kukreja, P Dhiman
2020 International conference on smart electronics and communication (ICOSEC …, 2020
1742020
Mustard Downy Mildew Disease Severity Detection using Deep Learning Model
R Sharma, V Kukreja
2021 international conference on decision aid sciences and application (DASA …, 2021
1392021
Revolutionizing Maize Disease Management with Federated Learning CNNs: A Decentralized and Privacy-Sensitive Approach
S Mehta, V Kukreja, A Gupta
2023 4th International Conference for Emerging Technology (INCET), 1-6, 2023
1212023
Adaptation of IoT with blockchain in Food Supply Chain Management: An analysis-based review in development, benefits and potential applications
A Kaur, G Singh, V Kukreja, S Sharma, S Singh, B Yoon
Sensors 22 (21), 8174, 2022
1082022
Empowering Farmers with AI: Federated Learning of CNNs for Wheat Diseases Multi-Classification
S Mehta, V Kukreja, S Vats
2023 4th International Conference for Emerging Technology (INCET), 1-6, 2023
1062023
Recent trends in mathematical expressions recognition: An LDA-based analysis
V Kukreja
Expert Systems with Applications 213, 119028, 2023
1052023
Detection of corn gray leaf spot severity levels using deep learning approach
A Baliyan, V Kukreja, V Salonki, KS Kaswan
2021 9th International conference on reliability, infocom technologies and …, 2021
1052021
Machine learning models for mathematical symbol recognition: A stem to stern literature analysis
V Kukreja, Sakshi
Multimedia Tools and Applications 81 (20), 28651-28687, 2022
1042022
Advanced mango leaf disease detection and severity analysis with federated learning and cnn
S Mehta, V Kukreja, R Yadav
2023 3rd International Conference on Intelligent Technologies (CONIT), 1-6, 2023
982023
Potato blight: deep learning model for binary and multi-classification
V Kukreja, A Baliyan, V Salonki, RK Kaushal
2021 8th International Conference on Signal Processing and Integrated …, 2021
962021
A novel GCL hybrid classification model for paddy diseases
S Lamba, A Baliyan, V Kukreja
International journal of Information technology 15 (2), 1127-1136, 2023
952023
Automatic classification of wheat rust diseases using deep convolutional neural networks
V Kukreja, D Kumar
2021 9th International Conference on Reliability, Infocom Technologies and …, 2021
952021
Recognition and classification of mathematical expressions using machine learning and deep learning methods
V Kukreja, S Ahuja
2021 9th International Conference on Reliability, Infocom Technologies and …, 2021
922021
Transforming Agriculture: Federated Learning CNNs for Wheat Disease Severity Assessment
S Mehta, V Kukreja, A Gupta
2023 8th International Conference on Communication and Electronics Systems …, 2023
882023
Deep learning in wheat diseases classification: A systematic review
D Kumar, V Kukreja
Multimedia Tools and Applications 81 (7), 10143-10187, 2022
882022
GAN-based synthetic data augmentation for increased CNN performance in Vehicle Number Plate Recognition
V Kukreja, D Kumar, A Kaur
2020 4th international conference on electronics, communication and …, 2020
872020
Hybrid fuzzy AHP–TOPSIS approach to prioritizing solutions for inverse reinforcement learning
V Kukreja
Complex & Intelligent Systems 9 (1), 493-513, 2023
862023
Image segmentation techniques: statistical, comprehensive, semi-automated analysis and an application perspective analysis of mathematical expressions
Sakshi, V Kukreja
Archives of Computational Methods in Engineering 30 (1), 457-495, 2023
862023
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