Zobrazeno 1 - 10
of 216
pro vyhledávání: '"Reich, Christoph"'
Resource-constrained hardware, such as edge devices or cell phones, often rely on cloud servers to provide the required computational resources for inference in deep vision models. However, transferring image and video data from an edge or mobile dev
Externí odkaz:
http://arxiv.org/abs/2404.12330
JPEG remains one of the most widespread lossy image coding methods. However, the non-differentiable nature of JPEG restricts the application in deep learning pipelines. Several differentiable approximations of JPEG have recently been proposed to addr
Externí odkaz:
http://arxiv.org/abs/2309.06978
Autor:
Reich, Christoph, Debnath, Biplob, Patel, Deep, Prangemeier, Tim, Cremers, Daniel, Chakradhar, Srimat
Standardized lossy video coding is at the core of almost all real-world video processing pipelines. Rate control is used to enable standard codecs to adapt to different network bandwidth conditions or storage constraints. However, standard video code
Externí odkaz:
http://arxiv.org/abs/2308.16215
Segmenting cells and tracking their motion over time is a common task in biomedical applications. However, predicting accurate instance-wise segmentation and cell motions from microscopy imagery remains a challenging task. Using microstructured envir
Externí odkaz:
http://arxiv.org/abs/2308.12116
Extracting single-cell information from microscopy data requires accurate instance-wise segmentations. Obtaining pixel-wise segmentations from microscopy imagery remains a challenging task, especially with the added complexity of microstructured envi
Externí odkaz:
http://arxiv.org/abs/2304.07597
Autor:
Gul, Ahmet Gokberk, Cetin, Oezdemir, Reich, Christoph, Prangemeier, Tim, Flinner, Nadine, Koeppl, Heinz
Publikováno v:
Proc. SPIE 12039, Medical Imaging 2022: Digital and Computational Pathology, 120391O (4 April 2022)
Whole Slide Image (WSI) analysis is a powerful method to facilitate the diagnosis of cancer in tissue samples. Automating this diagnosis poses various issues, most notably caused by the immense image resolution and limited annotations. WSIs commonly
Externí odkaz:
http://arxiv.org/abs/2210.09021
With the increased availability of 3D data, the need for solutions processing those also increased rapidly. However, adding dimension to already reliably accurate 2D approaches leads to immense memory consumption and higher computational complexity.
Externí odkaz:
http://arxiv.org/abs/2112.03917
Distributed machine learning algorithms that employ Deep Neural Networks (DNNs) are widely used in Industry 4.0 applications, such as smart manufacturing. The layers of a DNN can be mapped onto different nodes located in the cloud, edge and shop floo
Externí odkaz:
http://arxiv.org/abs/2111.05190
Convolutional neural networks (CNNs) are the current state-of-the-art meta-algorithm for volumetric segmentation of medical data, for example, to localize COVID-19 infected tissue on computer tomography scans or the detection of tumour volumes in mag
Externí odkaz:
http://arxiv.org/abs/2110.10640
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. Such experiments are costly, complex and labour intensive. A compl
Externí odkaz:
http://arxiv.org/abs/2106.08285