Browsing College of Engineering (MU) by Thesis Advisor "He, Zhihai"
Now showing items 1-7 of 7
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Accurate and robust animal species classification in the wild
(University of Missouri--Columbia, 2020)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI--COLUMBIA AT REQUEST OF AUTHOR.] Wildlife monitoring with camera-traps allows us to collect data at large scales in space and time to study the impact of climate changes, ... -
Deep learning with very few and no labels
(University of Missouri--Columbia, 2021)Deep neural networks have achieved remarkable performance in many computer vision applications such as image classification, object detection, instance segmentation, image retrieval, and person re-identification. However, ... -
Deep neural networks for animal object detection and recognition in the wild
(University of Missouri--Columbia, 2019)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Camera traps are a popular tool to sample animal populations because they are noninvasive, detect a variety of species, and can record many thousands ... -
Human behavior understanding and intention prediction
(University of Missouri--Columbia, 2020)Human motion, behaviors, and intention are governed by human perception, reasoning, common-sense rules, social conventions, and interactions with others and the surrounding environment. Humans can effectively predict ... -
Learning human poses in natural scenes
(University of Missouri--Columbia, 2018)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The task of human pose estimation in natural scenes is to determine the precise pixel locations of body keypoints. It is very important for many ... -
Reliable and structural deep neural networks
(University of Missouri--Columbia, 2022)Deep neural networks have dominated a wide range of computer vision research recently. However, recent studies have shown that deep neural networks are sensitive to adversarial perturbations. The limitations of deep networks ... -
Towards real-time object detection on edge with deep neural networks
(University of Missouri--Columbia, 2018)Despite being a core topic for more than several decades, object detection is still receiving increasing attentions due to its irreplaceable importance in a wide variety of applications. Abundant object detectors based on ...