Tobias Schlosser

Orcid: 0000-0002-0682-4284

According to our database1, Tobias Schlosser authored at least 10 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Attention Modules Improve Modern Image-Level Anomaly Detection: A DifferNet Case Study.
CoRR, 2024

Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case Study.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2022
Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks.
J. Intell. Manuf., 2022

Visual Acuity Prediction on Real-Life Patient Data Using a Machine Learning Based Multistage System.
CoRR, 2022

2020
Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning.
Proceedings of the 46th Annual Conference of the IEEE Industrial Electronics Society, 2020

Biologically Inspired Hexagonal Deep Learning For Hexagonal Image Generation.
Proceedings of the IEEE International Conference on Image Processing, 2020

2019
University of Applied Sciences Mittweida and Chemnitz University of Technology at TRECVID ActEv 2019.
Proceedings of the 2019 TREC Video Retrieval Evaluation, 2019

Hexagonal Image Processing in the Context of Machine Learning: Conception of a Biologically Inspired Hexagonal Deep Learning Framework.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

A Novel Visual Fault Detection and Classification System for Semiconductor Manufacturing Using Stacked Hybrid Convolutional Neural Networks.
Proceedings of the 24th IEEE International Conference on Emerging Technologies and Factory Automation, 2019

2016
Simplifying Accessibility Without Data Loss: An Exploratory Study on Object Preserving Keyframe Culling.
Proceedings of the Universal Access in Human-Computer Interaction. Users and Context Diversity, 2016


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