most citedDeep Learning Techniques for Geospatial Data Analysis

26 citations · 80 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI202122 cited

Classifications of the Summative Assessment for Revised Blooms Taxonomy by using Deep Learning

Manjushree D. Laddha, Varsha T. Lokare, Arvind W. Kiwelekar +1

Education is the basic step of understanding the truth and the preparation of the intelligence to reflect. Focused on the rational capacity of the human being the Cognitive process…

cs.CY20216 cited

A Decentralized and Autonomous Model to Administer University Examinations

Yogesh N Patil, Arvind W Kiwelekar, Laxman D Netak +1

Administering standardized examinations is a challenging task, especially for those universities for which colleges affiliated to it are geographically distributed over a wide area…

cs.CR202126 cited

Blockchain-based Security Services for Fog Computing

Arvind W. Kiwelekar, Pramod Patil, Laxman D. Netak +1

Fog computing is a paradigm for distributed computing that enables sharing of resources such as computing, storage and network services. Unlike cloud computing, fog computing platf…

cs.CY2020

Use-cases of Blockchain Technology for Humanitarian Engineering

Arvind W. Kiwelekar, Sanil S. Gandhi, Laxaman D. Netak +1

Humanitarian Engineers need innovative methods to make technological interventions for solving societal problems. The emerging blockchain technology has the enormous potential to p…

cs.AI202026 cited

Deep Learning Techniques for Geospatial Data Analysis

Arvind W. Kiwelekar, Geetanjali S. Mahamunkar, Laxman D. Netak +1

Consumer electronic devices such as mobile handsets, goods tagged with RFID labels, location and position sensors are continuously generating a vast amount of location enriched dat…