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Found 12 papers, 5 papers with code
MLOps for Scarce Image Data: A Use Case in Microscopic Image Analysis
The operationalization of ML models is governed by a set of concepts and methods referred to as Machine Learning Operations (MLOps).
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome.
EasyMLServe: Easy Deployment of REST Machine Learning Services
We contribute an EasyMLServe software framework to deploy machine learning services in the cloud using REST interfaces and generic local or web-based GUIs.
A universal synthetic dataset for machine learning on spectroscopic data
To assist in the development of machine learning methods for automated classification of spectroscopic data, we have generated a universal synthetic dataset that can be used for model validation.
ciscNet -- A Single-Branch Cell Instance Segmentation and Classification Network
Automated cell nucleus segmentation and classification are required to assist pathologists in their decision making.
Methods for the frugal labeler: Multi-class semantic segmentation on heterogeneous labels
This paper discusses the effects of frugal labeling and proposes to train neural networks for multi-class semantic segmentation on heterogeneously labeled data based on a novel objective function.
Ranked #1 on
2D Semantic Segmentation
on Extended heartSeg
Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks
Recent research in the field of computer vision strongly focuses on deep learning architectures to tackle image processing problems.
Towards DeepSpray: Using Convolutional Neural Network to post-process Shadowgraphy Images of Liquid Atomization
This technical report investigates the potential of Convolutional Neural Networks to post-process images from primary atomization.
Distributed traffic light control at uncoupled intersections with real-world topology by deep reinforcement learning
Different strategies, containing fixed-time, gap-based and time-based control approaches as well as our deep reinforcement learning based control approach, are implemented and assessed.
Transfer Learning versus Multi-agent Learning regarding Distributed Decision-Making in Highway Traffic
Transportation and traffic are currently undergoing a rapid increase in terms of both scale and complexity.
The MATLAB Toolbox SciXMiner: User's Manual and Programmer's Guide
The decision to a Matlab-based solution was made to use the wide mathematical functionality of this package provided by The Mathworks Inc. SciXMiner is controlled by a graphical user interface (GUI) with menu items and control elements like popup lists, checkboxes and edit elements.
Datenqualität in Regressionsproblemen
Further, the distribution of input data influences the reliability of regression models.
