Search Results for author:
Found 10 papers, 8 papers with code
Deep Video Codec Control for Vision Models
To overcome the deterioration of vision performance, this paper presents the first end-to-end learnable deep video codec control that considers both bandwidth constraints and downstream deep vision performance, while adhering to existing standardization.
The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures
In this paper, we introduce the trapped yeast cell (TYC) dataset, a novel dataset for understanding instance-level semantics and motions of cells in microstructures.
An Instance Segmentation Dataset of Yeast Cells in Microstructures
The aim of the dataset and evaluation strategy is to facilitate the development of new cell segmentation approaches.
Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak Labels
Here, we propose Self-ViT-MIL, a novel approach for classifying and localizing cancerous areas based on slide-level annotations, eliminating the need for pixel-wise annotated training data.
Histopathological Image Classification
Image Classification
+1
Yeast cell segmentation in microstructured environments with deep learning
We give an overview of the datasets recorded for training, validating and testing the networks, as well as a typical use-case.
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data
Occupancy networks (O-Nets) are an alternative for which the data is represented continuously in a function space and 3D shapes are learned as a continuous decision boundary.
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
Time-lapse fluorescent microscopy (TLFM) combined with predictive mathematical modelling is a powerful tool to study the inherently dynamic processes of life on the single-cell level.
Ranked #1 on
TFLM sequence generation
on TLFM dataset
Maximizing Information Gain for the Characterization of Biomolecular Circuits
Quantitatively predictive models of biomolecular circuits are important tools for the design of synthetic biology and molecular communication circuits.
Attention-Based Transformers for Instance Segmentation of Cells in Microstructures
For the specific use case, the proposed method surpasses the state-of-the-art tools for semantic segmentation and additionally predicts the individual object instances.
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning
Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data.
