Image classification is one of AI’s most common tasks, where a system is required to recognize an object from a given image. Yet real life requires us to recognize not a single standalone object but ...

This project implements a comprehensive Computer Vision MLOps pipeline for aerial object analysis, specifically designed to classify and detect birds vs drones in aerial imagery. The system combines: ...

Abstract: 3D classification is complex and challenging because of high-dimensional data, the intricate nature of their spatial relationships, and viewpoint variations. We fill the gap in view-based 3D ...

Abstract This project develops a deep learning-based solution to classify aerial images into two categories — Bird or Drone — and optionally perform object detection using YOLOv8. The system addresses ...

Object recognition through random scattering media has been an important but challenging task in many fields, such as biomedical imaging, oceanography, security, robotics, and autonomous driving.

Abstract: Deep object classification is an effective method for land-cover classification in remote sensing images, requiring fewer samples and achieving clearer classification boundaries. However, ...