Now showing items 1-5 of 5
Classification of Faults in Railway Ties Using Computer Vision and Machine Learning
(Virginia Tech, 2017-06-30)
This work focuses on automated classification of railway ties based on their condition using aerial imagery. Four approaches are explored and compared to achieve this goal - handcrafted features, HOG features, transfer ...
A Computer-Aided Framework for Cell Phenotype Identification, Analysis and Classification
(Virginia Tech, 2017-09-11)
Cancer is arguably one of the most dangerous diseases and the major causes of death in the modern day. It becomes increasingly harder to treat and cure the disease as it makes progress. Detecting cancer at an early stage ...
Deep Learning Models for Context-Aware Object Detection
(Virginia Tech, 2017-09-15)
In this thesis, we present ContextNet, a novel general object detection framework for incorporating context cues into a detection pipeline. Current deep learning methods for object detection exploit state-of-the-art image ...
Role of Premises in Visual Question Answering
(Virginia Tech, 2017-06-12)
In this work, we make a simple but important observation questions about images often contain premises -- objects and relationships implied by the question -- and that reasoning about premises can help Visual Question ...
The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions
(Virginia Tech, 2017-07-12)
As research in Artificial Intelligence (AI) advances, it is crucial to focus on having seamless communication between humans and machines in order to effectively accomplish tasks. Smooth human-machine communication requires ...