Recent advancements in computer vision have enabled wide-ranging applications in every
field of life. One such application area is fresh produce classification, but the classification of …

Feature matching, which refers to establishing reliable correspondence between two sets of
features (particularly point features), is a critical prerequisite in feature-based registration. In …

Inferring topological and geometrical information from data can offer an alternative
perspective in machine learning problems. Methods from topological data analysis, eg …

Automated systems for plant recognition can be used to classify plants into appropriate
taxonomies. Such information can be useful for botanists, industrialists, food engineers and …

Neural network representation learning for spatial data (eg, points, polylines, polygons, and
networks) is a common need for geographic artificial intelligence (GeoAI) problems. In …

We consider the problem of supervised learning with summary representations of
topological features in data. In particular, we focus on persistent homology, the prevalent …

Low-textured image stitching remains a challenging problem. It is difficult to achieve good
alignment of images and it is easy to break images structures are often broken due to …

Feature engineering takes a very important role in writer identification which has been
widely studied in the literature. Previous works have shown that the joint feature distribution …

In this work we propose a new online, low cost and fast approach based on computer vision
and machine learning to determine whether cutting tools used in edge profile milling …

Color, as a notable and stable attribute of vehicles, can serve as a useful and reliable cue in
a variety of applications in intelligent transportation systems. Therefore, vehicle color …