Ahmad Fashiha Hastawan
Papers
1
Total Citations
2
H-Index
1
About
Ahmad Fashiha Hastawan is a researcher whose work centers on computer vision and pattern recognition, with a particular focus on geometric shape identification. His key contribution lies in developing robust methods for detecting and recognizing two-dimensional planar objects, a fundamental challenge in automated visual systems. His most cited paper, "Deteksi Sudut Menggunakan Kode Rantai untuk Pengenalan Bangun Datar Dua Dimensi" (2013), introduces a novel approach that leverages chain codes for corner detection to enable consistent shape recognition, even in the presence of visual disturbances. This work addresses the critical need for reliable computer vision systems capable of identifying objects with specific geometric characteristics. While his citation count is modest, his research lays important groundwork for applications in industrial automation, robotics, and document analysis where accurate shape recognition is essential. Hastawan’s contributions demonstrate a focused effort to solve core problems in image processing, providing foundational techniques that can be built upon for more complex visual recognition tasks. His work represents a practical step toward creating more resilient and accurate computer vision systems.
Research Focus
Key Achievements
Top Papers
- 1