Sökning: "Object segmentation"

Visar resultat 11 - 15 av 135 uppsatser innehållade orden Object segmentation.

1. 11. Point clouds in the application of Bin Picking

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Abhijeet Anand; [2023]
   Nyckelord :Point clouds; Computer vision; 3D instance segmentation; Point cloud registration; Deep learning; Clustering;

   Sammanfattning : Automatic bin picking is a well-known problem in industrial automation and computer vision, where a robot picks an object from a bin and places it somewhere else. There is continuous ongoing research for many years to improve the contemporary solution. LÄS MER

3. 12. Structure from Motion with a Neural Network

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Jiarong Gong; [2023]
   Nyckelord :Technology and Engineering;

   Sammanfattning : This project delves into the 3D reconstruction of both single and multiple rigid motions, examining the potential of deep learning methods, such as that proposed by Moran et al., to supplant traditional geometry-based approaches. The project is structured into two main parts. LÄS MER

4. 13. Integration of Continual Learning and Semantic Segmentation in a vision system for mobile robotics

   Master-uppsats, Luleå tekniska universitet/Rymdteknik

   Författare :Cristian David Echeverry Valencia; [2023]
   Nyckelord :Continual Learning; Progressive Neural Networks; mobile robotics; Computer Vision; Machine Learning; Semantic Segmentation;

   Sammanfattning : Over the last decade, the integration of robots into various applications has seen significant advancements fueled by Machine Learning (ML) algorithms, particularly in autonomous and independent operations. While robots have become increasingly proficient in various tasks, object instance recognition, a fundamental component of real-world robotic interactions, has witnessed remarkable improvements in accuracy and robustness. LÄS MER

5. 14. Instance Segmentation for Printed Circuit Board (PCB) Component Analysis : Exploring CNNs and Transformers for Component Detection on Printed Circuit Boards

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Oliver Möller; [2023]
   Nyckelord :Deep Learning; Computer Vision; Image Processing; Object Detection; Instance Segmentation; Printed Circuit Board PCB ; Djupinlärning; Datorseende; Bildbehandling; Objektdetektering; Instanssegmentering; Tryckt kretskort;

   Sammanfattning : In the intricate domain of Printed Circuit Boards (PCBs), object detection poses unique challenges, particularly given the broad size spectrum of components, ranging from a mere 2 pixels to several thousand pixels within a single high-resolution image, often averaging 4000x3000 pixels. Such resolutions are atypical in the realm of deep learning for computer vision, making the task even more demanding. LÄS MER

7. 15. Analyzing different approaches to Visual SLAM in dynamic environments : A comparative study with focus on strengths and weaknesses

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Kristín Sól Ólafsdóttir; [2023]
   Nyckelord :Visual SLAM; RGB-D Vision; Dynamic Objects; Object Detection; Multi-Object Tracking; Image Segmentation; Optical Flow; Visual SLAM; RGB-D Syn; Dynamiska objekt; Objektdetektering; Multi-Objekt Spårning; Bildsegmentation; Optiskt Flöde;

   Sammanfattning : Simultaneous Localization and Mapping (SLAM) is the crucial ability for many autonomous systems to operate in unknown environments. In recent years SLAM development has focused on achieving robustness regarding the challenges the field still faces e.g. dynamic environments. LÄS MER