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Sunil Kumar on Muck Rack

Sunil Kumar

As seen in: Bangalore Mirror, ET Healthworld, Forbes, Nature, The Economic Times, The Times of India, India Times, Science Magazine, Capgemini, Cell Press and

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Articles

Impact of crop establishment practices and herbicide sequencing on weed control, maize productivity, and soil microbial dynamics

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By Sunil Kumar, Ramanjit Kaur, T. Das, Seema Sepat, Teekam Singh, Anchal Dass, S. L. Meena, Dileep Meena, Sk Asraful Ali, Shital Kumar, Seema Sangwan, R. S. Bana
| Nature Verified
Abstract Maize (Zea mays L.) is a globally important cereal cultivated across diverse agro-ecological regions due to its remarkable phenotypic plasticity and the highest genetic yield potential. Being a wet season crop in South Asia, weeds always remain a big challenge in harnessing its full potential.
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I must be the change: For reflection by study circles – who is responsible and accountable to imbibe constitutional fundamental duties, Article 51A?

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By Sunil Kumar
| The Times of India Verified
1. Education is fundamental for achieving full human potential, says the New Education Policy (NEP 20) and for “developing an equitable and just society”, “promoting national development”, “developing and maximizing our country’s rich talents and resources for the good of the individual, the society, the country, and the world”.
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DeepGreen: a real-time deep learning system for smart agriculture monitoring

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By Sushabhan Choudhury, Abhinav Sharma, Rupendra Kumar Pachauri, Gautam M. Shah, Nuzhat Fatema, Hasmat Malik, Vijay Sharma, Sunil Kumar, Ajit Singh Rathor
| Nature Verified
Abstract Plant diseases are a major problem for farmers around the world, reducing crop yields. The absence of expertise makes plant disease detection difficult and complicated. Plant disease detection is made easier by deep learning algorithms; however, they are computationally demanding and need huge training datasets. This research work proposes a novel Conv-7 DCNN model with modified ParNet attention layer to classify plant leaves into distinct categories with improved accuracy.
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