Anditya Arifianto
Papers
1
Total Citations
12
H-Index
1
About
Anditya Arifianto is a researcher at the forefront of applying deep learning and computer vision to agricultural automation. His work centers on developing intelligent systems for precision agriculture, with a particular focus on real-time plant classification and weed management. His most cited paper, "Real-Time Wheat Classification System for Selective Herbicides Using Broad Wheat Estimation in Deep Neural Network" (2019, 12 citations), addresses a critical bottleneck in modern farming: the time-consuming process of manual seed identification. By designing a deep neural network capable of accurately distinguishing wheat from weeds in real time, Arifianto’s system enables targeted herbicide application, reducing chemical usage and environmental impact. This contribution demonstrates how big data and advanced analytics can transform practical agricultural workflows, making selective herbicide treatment both economically and technically viable. His work bridges the gap between cutting-edge AI and real-world farming challenges, offering scalable solutions for sustainable crop management. With growing interest in smart agriculture, Arifianto’s research continues to influence the development of automated, data-driven tools that empower farmers to increase efficiency while minimizing ecological harm.
Research Focus
Key Achievements
Top Papers
- 1