Date of Award

12-2023

Degree Type

Thesis-Restricted

Degree Name

M.S.

Degree Program

Computer Science

Department

Computer Science

Major Professor

Atriya Sen

Abstract

We are more interested in recovering and salvaging containers which may be loaded with either valuable or harmful substances. Therefore, we designed various container models to account for different loading conditions and then exported them to a 3D printer. Six small container models were dropped into the trailer pool at the University of New Orleans (UNO) as planned at angles of 0°, 45°, and 90°.

After collecting all the videos using a high-definition camera set outside the tank, we perform pre-processing tasks on the videos in preparation for model training. The two-phase angle classification method uses a pretrained ResNet50 model trained on ImageNet as a feature extractor to generate latent features to train a gated recurrent unit (GRU) model to classify the entry angle of dropped objects.

Furthermore, the output of the recognition phase, including the shape of the dropped object and the initial drop angle, is used as input to another in-house tool, the Dropped Object Simulator (DROBS), which was developed in MATLAB using simulate the trajectory and determine the final landing position.

Rights

The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.

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