A Comprehensive Study on Object Detection Techniques in Unfettered Environments.

In computer vision, object detection is an essential task to identify and classify objects in the image or video. The recent advancements in deep learning and convolutional Neural Networks (CNNs) have significantly improved the performance of object detection techniques. In an unconstrained environment, the study in this paper provides a detailed analysis of object detection techniques and various challenges, datasets, or state-of-the-art approaches. In addition, a comparative analysis of these methods is presented and its strengths and weaknesses are highlighted. Finally, we've provided some new research directions for improving the detection of objects in uncontrolled environments. [ABSTRACT FROM AUTHOR]