Container damage detection and classification using container images
İmamoğlu, Zeynep, author.

Container damage detection and classification using container images

İmamoğlu, Zeynep, author.

Yazar Ek Girişi
İmamoğlu, Zeynep, author.

Fiziksel Tanımlama
x, 51 leaves: charts;+ 1 computer laser optical disc

In the logistics sector, digital transformation is of great importance in terms of competition. In the present case, container warehouse entry / exit operations are carried out manually by the logistics personnel including container damage detection. During container warehouse entry / exit process, the process of detecting damaged containers is carried out by the personnel and several minutes are required to upload to the system. The aim of this thesis is to automate detection of damaged containers. This way, the mistakes made by the personnel in this stage will be eliminated and the process will be accelerated. In this thesis, we propose a machine learning method which detects damaged containers using the container images to perform statistical damaged / undamaged estimation. We modeled the problem as a binary classification problem, which considers a container as damaged or undamaged. The result obtained from the undertaken studies shows that there is no single best method for visual classification. It is shown how the dataset was created and how the parameters used in the layered structure impact the most suitable model could be created for this study.

Konu Başlığı
Machine learning.

Yazar Ek Girişi
Tuğlular, Tuğkan

Tüzel Kişi Ek Girişi
İzmir Institute of Technology. Computer Engineering.

Tek Biçim Eser Adı
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
İzmir Institute of Technology: Computer Engineering--Thesis Master).

Elektronik Erişim
Access to Electronic Versiyon.

KütüphaneMateryal TürüDemirbaş NumarasıYer NumarasıDurumu/İade Tarihi
IYTETezT002060Q325.5 .I319 2019Tez Koleksiyonu