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Learning To Detect Pedestrians By Watching Videos, Andrew Y. Chen
Learning To Detect Pedestrians By Watching Videos, Andrew Y. Chen
Theses and Dissertations
The field of deep learning has experienced a resurgence in the recent years, particularly resulting with the advent of AlexNet. Supervised learning is currently the most common and practical machine learning method. The struggle with employing supervised learning to approach problems is that it requires training data. Sufficient training data is correlated with performance for deep learning models. The issue is that preparing the training data can be a tedious and labor intensive task, especially on a large scale. The purpose of this paper is to determine how efficient a machine can learn when trained on automatically annotated data. The …
Detecting Phone-Related Pedestrian Behavior Using A Two-Branch Convolutional Neural Network, Humberto Saenz
Detecting Phone-Related Pedestrian Behavior Using A Two-Branch Convolutional Neural Network, Humberto Saenz
Theses and Dissertations
With the wide use of smart phones, distraction has become a major safety concern to roadway users. The distracted phone-use behaviors among pedestrians, like Texting, Game Playing and Phone Calls, have caused increasing fatalities and serious injuries. With the increasing usage of driver monitor systems on intelligent vehicles, distracted driver behaviors can be efficiently detected and warned. However, the research of phone-related distracted behavior by pedestrians has not been systemically studied. It is desired to improve both the driving and pedestrian safety by automatically discovering the phone-related pedestrian distracted behaviors. In this thesis, we propose a new computer vision-based method …
Analysis Of The Cnn Algorithm In Target Recognition By Using The Mstar Database, Ligang Zou
Analysis Of The Cnn Algorithm In Target Recognition By Using The Mstar Database, Ligang Zou
Theses and Dissertations
With the rapid development of artificial intelligence technology and the emergence of a large number of innovative theories, the concept of deep learning is widely used in object detection, speech recognition, language translation and other fields. One of the important practices is target recognition in SAR images. Although it shows certain effectiveness in some researches, when using deep learning algorithm, there are still many problems that have not yet been solved. For example, people do not have a good understanding of how convolution works and the impact of convolution on the algorithm, although convolution works well in the CNN algorithm. …