Gheri Febri Ananda
Papers
1
Total Citations
10
H-Index
1
About
Gheri Febri Ananda is a rising researcher at the forefront of applying deep learning to environmental sustainability, with a primary focus on intelligent waste management systems. Her most impactful work, "Deep Learning-Based Waste Classification with Transfer Learning Using EfficientNet-B0 Model" (2024, 10 citations), addresses a critical bottleneck in modern recycling: the limitations of conventional proximity sensors in accurately identifying diverse waste types. By leveraging transfer learning with the EfficientNet-B0 architecture, Ananda has demonstrated a scalable, high-accuracy solution for automated waste sorting—a pressing need in Indonesia, which generates approximately 175,000 tons of waste daily. This contribution not only advances computer vision applications in environmental engineering but also offers a practical pathway to improving recycling rates in developing nations. Her work stands out for bridging the gap between state-of-the-art AI techniques and real-world waste management challenges, earning early recognition for its potential to transform municipal recycling infrastructure. Ananda’s research exemplifies how targeted deep learning innovations can drive tangible environmental impact, making her a promising voice in the intersection of artificial intelligence and sustainable development.
Research Focus
Key Achievements
Top Papers
- 1