DS
Dr. Aditya Shastri
Pandit Deendayal Energy University, Mukesh Patel School of Technology Management and Engineering - Shirpur Campus, Prof Ram Meghe Institute of Technology and Research
Research areas: Computer Science · Computational Theory and Mathematics · Complexity and Algorithms in Graphs · Advanced Graph Theory Research · Advanced Database Systems and Queries
Employment
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Pandit Deendayal Petroleum University Assistant Professor2022 - Present
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Mukesh Patel School of Technology Management and Engineering - Shirpur Campus Assistant Professor2020 - 2022
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Prof Ram Meghe Institute of Technology and Research Assistant Professor2015 - 2015
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (15)
- ENHANCING POTATO CROP HEALTH MONITORING USING TWO STAGE CNN BASED DISEASE CLASSIFICATION MODELS Save
- Improving Spectral Clustering Scalability Through Intelligent Sampling Methods Save
- Enhancing Clinical Outcomes Using Deep Learning Solution for Accurate Lung Cancer Classification Save
- Enhancing Pneumonia Detection Transparency: Exploring Explainable AI Model Save
- A Hyper-tuned Metrics based Augmented CNN Model for Accurate Prediction of Monkeypox Risk Save
- An ANOVA Based Analysis of Routing Techniques for Improving QoS in Flying Ad-Hoc Networks (FANETs) Save
- Intelligent Trolley System: Revolutionizing Retail Shopping Save
- IoT-Assisted Mushroom Cultivation in Agile Environment Save
- Cube Sampled K-Prototype Clustering for Featured Data Save
- Probabilistically sampled and spectrally clustered plant species using phenotypic characteristics Save
- An Apache Giraph Implementation of Distributed ADMM for Solving LASSO Problems Save
- Scaled and Projected Spectral Clustering with Vector Quantization for Handling Big Data Save
- Vector quantized spectral clustering applied to whole genome sequences of plants Save
- Density-wise two stage mammogram classification using texture exploiting descriptors Save
- Efficient and effective security model for database specially designed to avoid internal threats Save