Agricultural Land Mapping and Classification are among the most challenging tasks in the agricult... more Agricultural Land Mapping and Classification are among the most challenging tasks in the agricultural domain. Accurate prediction of agricultural land type in developing countries ahead of sowing is central to preventing famine, improving food security, and sustainable development of agriculture. Currently, leading agricultural land use prediction techniques mostly rely on locally sensed data, such as rainfall measurements and farmer surveys from field visits. Locally sensed data provide detailed information but are expensive to collect, often noisy, and extremely difficult to scale. Remote sensing and satellite imagery data, a cheap and globallyaccessible resource, coupled with modern machine learning approaches offer a potential solution. In this paper, we present a framework to work with remote sensing and satellite imagery data to categorize land regions in terms of their agricultural capabilities in order to maximize efficiency and productivity. Improving existing methods, we i...
International journal of engineering research and technology, 2020
Criminal activities have reached unprecedented levels in almost every part of the world. Desperat... more Criminal activities have reached unprecedented levels in almost every part of the world. Desperate times like these require desperate measures to ensure the safety of people, especially people that need to travel on a daily basis to places, known and unknown. The majority of these criminal offences occur while the victim is travelling, irrespective of the mode of transport: walking, personal vehicles, public transport vehicles, auto-rickshaws, or cabs. This paper proposes a UserSpecific Safe Route Recommendation System which presents a safe route visualized on maps to the user based on the past criminal records of the geographical region. Our approach is implemented on two-levels, first to realize the user-specific features using a Decision Network and the latter to actuate the safe route generation using Geospatial Data Analysis. We visualize the determined routes through a colour-code based map interface. Keeping in mind the real-life impact our project needs to create; we have de...
International Journal of Recent Technology and Engineering
Text Summarization is the technique in which the source document is simplified, valuable informat... more Text Summarization is the technique in which the source document is simplified, valuable information is distilled and an abridged version is produced. Over the last decade, the focus has shifted from single document to multi-document summarization and despite significant progress in the domain, challenges such as sentence ordering and fluency remain. In this paper, a thorough comparison of the several multi-document text summarization techniques such as Machine Learning based, Graph based, Game-Theory based and more has been presented. This paper in its entirety condenses and interprets the numerous approaches, merits and limitations of these techniques. The Benchmark datasets of this domain and their features have also been examined. This survey aims to distinguish the various summarization algorithms based on properties that prove to be valuable in the generation of highly consistent, rational, summaries with reduced redundancy and information richness. The conclusions presented b...
Agricultural Land Mapping and Classification are among the most challenging tasks in the agricult... more Agricultural Land Mapping and Classification are among the most challenging tasks in the agricultural domain. Accurate prediction of agricultural land type in developing countries ahead of sowing is central to preventing famine, improving food security, and sustainable development of agriculture. Currently, leading agricultural land use prediction techniques mostly rely on locally sensed data, such as rainfall measurements and farmer surveys from field visits. Locally sensed data provide detailed information but are expensive to collect, often noisy, and extremely difficult to scale. Remote sensing and satellite imagery data, a cheap and globallyaccessible resource, coupled with modern machine learning approaches offer a potential solution. In this paper, we present a framework to work with remote sensing and satellite imagery data to categorize land regions in terms of their agricultural capabilities in order to maximize efficiency and productivity. Improving existing methods, we i...
International journal of engineering research and technology, 2020
Criminal activities have reached unprecedented levels in almost every part of the world. Desperat... more Criminal activities have reached unprecedented levels in almost every part of the world. Desperate times like these require desperate measures to ensure the safety of people, especially people that need to travel on a daily basis to places, known and unknown. The majority of these criminal offences occur while the victim is travelling, irrespective of the mode of transport: walking, personal vehicles, public transport vehicles, auto-rickshaws, or cabs. This paper proposes a UserSpecific Safe Route Recommendation System which presents a safe route visualized on maps to the user based on the past criminal records of the geographical region. Our approach is implemented on two-levels, first to realize the user-specific features using a Decision Network and the latter to actuate the safe route generation using Geospatial Data Analysis. We visualize the determined routes through a colour-code based map interface. Keeping in mind the real-life impact our project needs to create; we have de...
International Journal of Recent Technology and Engineering
Text Summarization is the technique in which the source document is simplified, valuable informat... more Text Summarization is the technique in which the source document is simplified, valuable information is distilled and an abridged version is produced. Over the last decade, the focus has shifted from single document to multi-document summarization and despite significant progress in the domain, challenges such as sentence ordering and fluency remain. In this paper, a thorough comparison of the several multi-document text summarization techniques such as Machine Learning based, Graph based, Game-Theory based and more has been presented. This paper in its entirety condenses and interprets the numerous approaches, merits and limitations of these techniques. The Benchmark datasets of this domain and their features have also been examined. This survey aims to distinguish the various summarization algorithms based on properties that prove to be valuable in the generation of highly consistent, rational, summaries with reduced redundancy and information richness. The conclusions presented b...
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Papers by Yash Asawa