Abstract Although Domain Adaptation in Semantic Scene Segmentation has shown
impressive improvement in recent years, the fairness concerns in the domain adaptation …

In precision agriculture the detection and recognition of insects play an essential role in the
ability of crops to grow healthy and produce a high-quality yield. The current machine vision …

We focus on domain adaptation, a branch of transfer learning that concentrates on
transferring knowledge from one domain to another when the data distributions differ …

Unsupervised domain adaptation (UDA) is a well-explored domain in transfer learning,
finding applications across various real-world scenarios. The central challenge in UDA lies …

In the food industry, assessing the quality of poultry carcasses during processing is a crucial
step. This study proposes an effective approach for automating the assessment of carcass …

In traditional machine learning, the training and testing data are assumed to come from the
same independent and identical distributions. This assumption, however, does not hold up …

Engineers prefer deep neural networks (DNNs) for solving computer vision problems.
However, DNNs pose two major problems. First, neural networks require large amounts of …