2025-03-01 –, Swami Vivekananda Auditorium
India's agriculture sector faces significant challenges due to unpredictable crop damage, directly impacting farmers' livelihoods and insurance claim processes. In this talk, we introduce KishanRakshak, an innovative AI-driven framework leveraging transfer learning to classify and predict rice crop damage with high accuracy.
Using image captured by farmers KishanRakshak achieves efficient damage estimation tailored to India's diverse agro-climatic regions. This framework not only streamlines insurance claim evaluations but also empowers policymakers and insurers to optimize response strategies, enhancing resilience in the agriculture sector.
Join this session to explore how AI and transfer learning are transforming crop damage assessment, paving the way for sustainable farming and smarter insurance solutions in India.
AIforAgriculture #CropDamagePrediction #KishanRakshak #SustainableFarming #TransferLearning
Intermediate - attendees should be familiar with the subject
Sourav Bera is a Solutions Architect at Microsoft and a machine learning researcher, holding certifications in CKA, CKAD, CKS, LFCS, LFCT and 11x Azure and GCP. He is passionate about modern architectures, microservices, and security with AI. As a Hackathon jury, community speaker, and builder, Sourav has presented at key events like CNCF Community Days, the IEEE Leadership Summit, and the Microsoft Reactor Program.