Dataset for Anomalies Detection in 3D Printing

Image Dataset for Visual Objects Classification in 3D Printing

The rapid development in additive manufacturing (AM), also known as 3D printing, has brought about potential risk and security issues along with significant benefits. In order to enhance the security level of the 3D printing process, the present research aims to detect and recognize illegal components using deep learning. In this work, we collected a dataset of 61,340 2D images (28×28 for each ...

Detection of Congenital Mullerian Anomalies Using Real-Time 3D Sonography

Thingi10K: A Dataset of 10, 000 3D-Printing Models

Empirically validating new 3D-printing related algorithms and implementations requires testing data representative of inputs encountered in the wild. An ideal benchmarking dataset should not only draw from the same distribution of shapes people print in terms of class (e.g., toys, mechanisms, jewelry), representation type (e.g., triangle soup meshes) and complexity (e.g., number of facets), but...

metrics for the detection of changed buildings in 3d old vector maps using als data (case study: isfahan city)

هدف از این تحقیق، ارزیابی و بهبود متریک های موجود جهت تایید صحت نقشه های قدیمی سه بعدی برداری با استفاده از ابر نقطه حاصل از لیزر اسکن جدید شهر اصفهان می باشد . بنابراین ابر نقطه حاصل از لیزر اسکنر با چگالی حدودا سه نقطه در هر متر مربع جهت شناسایی عوارض تغییر کرده در نقشه های قدیمی سه بعدی استفاده شده است. تمرکز ما در این تحقیق بر روی ساختمان به عنوان یکی از اصلی ترین عارضه های شهری می باشد. من...

Vision based error detection for 3D printing processes

3D printers became more popular in the last decade, partly because of the expiration of key patents and the supply of affordable machines. The origin is located in rapid prototyping. With Additive Manufacturing (AM) it is possible to create physical objects from 3D model data by layer wise addition of material. Besides professional use for prototyping and low volume manufacturing they are becom...