Mathis Hoffmann
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View article: Addressing data scarcity in nanomaterial segmentation networks with differentiable rendering and generative modeling
Addressing data scarcity in nanomaterial segmentation networks with differentiable rendering and generative modeling Open
Nanomaterials’ properties, influenced by size, shape, and surface characteristics, are crucial for their technological, biological, and environmental applications. Accurate quantification of these materials is essential for advancing resea…
View article: Addressing data scarcity in nanomaterial segmentation networks with differentiable rendering and generative modeling
Addressing data scarcity in nanomaterial segmentation networks with differentiable rendering and generative modeling Open
Nanomaterials’ properties, influenced by size, shape, and surface characteristics, are crucial for their technological, biological, and environmental applications. Accurate quantification of these materials is essential for advancing resea…
View article: Optimizing neurointerventional procedures: an algorithm for embolization coil detection and automated collimation to enable dose reduction
Optimizing neurointerventional procedures: an algorithm for embolization coil detection and automated collimation to enable dose reduction Open
To our knowledge, this marks the initial attempt at an approach successfully detecting embolization coils, showcasing the extended applications of integrating detection results into the X-ray angiography system. The method we present has t…
View article: Anomaly detection in IR images of PV modules using supervised contrastive learning
Anomaly detection in IR images of PV modules using supervised contrastive learning Open
Increasing deployment of photovoltaic (PV) plants requires methods for automatic detection of faulty PV modules in modalities, such as infrared (IR) images. Recently, deep learning has become popular for this. However, related works typica…
View article: Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning Open
Increasing deployment of photovoltaic (PV) plants requires methods for automatic detection of faulty PV modules in modalities, such as infrared (IR) images. Recently, deep learning has become popular for this. However, related works typica…
View article: Module-Power Prediction from PL Measurements using Deep Learning
Module-Power Prediction from PL Measurements using Deep Learning Open
The individual causes for power loss of photovoltaic modules are investigated for quite some time. Recently, it has been shown that the power loss of a module is, for example, related to the fraction of inactive areas. While these areas ca…
View article: Deep‐learning‐based pipeline for module power prediction from electroluminescense measurements
Deep‐learning‐based pipeline for module power prediction from electroluminescense measurements Open
Automated inspection plays an important role in monitoring large‐scale photovoltaic power plants. Commonly, electroluminescense measurements are used to identify various types of defects on solar modules, but have not been used to determin…
View article: Joint Superresolution and Rectification for Solar Cell Inspection
Joint Superresolution and Rectification for Solar Cell Inspection Open
Visual inspection of solar modules is an important monitoring facility in\nphotovoltaic power plants. Since a single measurement of fast CMOS sensors is\nlimited in spatial resolution and often not sufficient to reliably detect small\ndefe…
View article: Deep Learning-based Pipeline for Module Power Prediction from EL\n Measurements
Deep Learning-based Pipeline for Module Power Prediction from EL\n Measurements Open
Automated inspection plays an important role in monitoring large-scale\nphotovoltaic power plants. Commonly, electroluminescense measurements are used\nto identify various types of defects on solar modules but have not been used to\ndeterm…
View article: Deep Learning-based Pipeline for Module Power Prediction from EL Measurements
Deep Learning-based Pipeline for Module Power Prediction from EL Measurements Open
Automated inspection plays an important role in monitoring large-scale photovoltaic power plants. Commonly, electroluminescense measurements are used to identify various types of defects on solar modules but have not been used to determine…
View article: Weakly Supervised Segmentation of Cracks on Solar Cells using Normalized Lp Norm
Weakly Supervised Segmentation of Cracks on Solar Cells using Normalized Lp Norm Open
Photovoltaic is one of the most important renewable energy sources for dealing with world-wide steadily increasing energy consumption. This raises the demand for fast and scalable automatic quality management during production and operatio…
View article: Weakly Supervised Segmentation of Cracks on Solar Cells using Normalized\n Lp Norm
Weakly Supervised Segmentation of Cracks on Solar Cells using Normalized\n Lp Norm Open
Photovoltaic is one of the most important renewable energy sources for\ndealing with world-wide steadily increasing energy consumption. This raises the\ndemand for fast and scalable automatic quality management during production and\nopera…
View article: Calibration‐free beam hardening reduction in x‐ray CBCT using the epipolar consistency condition and physical constraints
Calibration‐free beam hardening reduction in x‐ray CBCT using the epipolar consistency condition and physical constraints Open
Background The beam hardening effect is a typical source of artifacts in x‐ray cone beam computed tomography (CBCT). It causes streaks in reconstructions and corrupted Hounsfield units toward the center of objects, widely known as cupping …
View article: A Robust Chessboard Detector for Geometric Camera Calibration
A Robust Chessboard Detector for Geometric Camera Calibration Open
We introduce an algorithm that detects chessboard patterns in images precisely and robustly for application in camera calibration. Because of the low requirements on the calibration images, our solution is particularly suited for endoscopi…