Image Annotation
Image annotation, the process of labeling images with information like object boundaries, classes, or attributes, is crucial for training computer vision models. Current research emphasizes improving annotation efficiency and accuracy through active learning techniques, deep learning architectures (especially convolutional neural networks), and the integration of foundation models for automated labeling. This work is significant because efficient and accurate annotation is essential for advancing various applications, including medical image analysis, remote sensing, and autonomous navigation, where large, high-quality datasets are needed to train robust and reliable models.
Papers
Automatic Image Annotation (AIA) of AlmondNet-20 Method for Almond Detection by Improved CNN-based Model
Mohsen Asghari Ilani, Saba Moftakhar Tehran, Ashkan Kavei, Arian Radmehr
CNN-based Labelled Crack Detection for Image Annotation
Mohsen Asghari Ilani, Leila Amini, Hossein Karimi, Maryam Shavali Kuhshuri