• Accurate and robust animal species classification in the wild 

    Ahmed, Ahmed Qasim (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 

    Li, Yang (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 

    Yousif, Hayder (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 

    Sun, Hao (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 

    Ning, Guanghan (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 

    Yuan, Jianhe (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 

    Zhang, Zhi (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 ...