The YOLO series has become the most popular framework for real-time object detection due
to its reasonable trade-off between speed and accuracy. However we observe that the …

In this paper, we propose a new operator, called 3D DeFormable Attention (DFA3D), for 2D-
to-3D feature lifting, which transforms multi-view 2D image features into a unified 3D space …

Pseudo-labeling is significant for semi-supervised instance segmentation, which generates
instance masks and classes from unannotated images for subsequent training. However, in …

Quality assessment in industrial applications is often carried out through visual inspection,
usually performed or supported by human domain experts. However, the manual visual …

A revealing genealogy of image-recognition techniques and technologies Today's most
advanced neural networks and sophisticated image-analysis methods come from 1950s …

The automatic analysis of images in the historical sciences often requires the identification of
objects. Object identification is a well-researched problem for modern photographs; …

The attribution of the author of an art piece is typically a laborious manual process, usually
relying on subjective evaluations of expert figures. However, there are some situations in …

Remote sensing object detection remains a challenging task in computer vision due to the
arbitrary angles of the targets and the complex environmental conditions, which contribute to …

The chapter focuses on exploring various challenges and deep learning (DL) techniques
used in text detection and recognition. It offers a detailed analysis of different deep models …

Wheat is one of the most important cereal crops, contributing significantly to the financial
economy and food sources. Currently, the direct consumption of wheat amounts to about …