Christoph Käding
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View article: Lessons learned after one year of COVID-19 from a urologist and radiotherapist view: A German survey on prostate cancer diagnosis and treatment
Lessons learned after one year of COVID-19 from a urologist and radiotherapist view: A German survey on prostate cancer diagnosis and treatment Open
Introduction Since the beginning of the pandemic in 2020, COVID-19 has changed the medical landscape. International recommendations for localized prostate cancer (PCa) include deferred treatment and adjusted therapeutic routines. Materials…
View article: Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research—Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apes
Pre-trained models are not enough: active and lifelong learning is important for long-term visual monitoring of mammals in biodiversity research—Individual identification and attribute prediction with image features from deep neural networks and decoupled decision models applied to elephants and great apes Open
Animal re-identification based on image data, either recorded manually by photographers or automatically with camera traps, is an important task for ecological studies about biodiversity and conservation that can be highly automatized with…
View article: A Benchmark for Bivariate Causal Discovery Methods
A Benchmark for Bivariate Causal Discovery Methods Open
<p>The Earth&#8217;s climate is a highly complex and dynamical system. To better understand and robustly predict it, knowledge about its underlying dynamics and causal dependency structure is required. Since controlled experiment…
View article: A case of giant retroperitoneal lymphangioma and IgG4-positive fibrosis: Causality or coincidence?
A case of giant retroperitoneal lymphangioma and IgG4-positive fibrosis: Causality or coincidence? Open
Several chronic inflammatory diseases have been found to be a subtype of IgG4-related disease, all of which have a typical clinical and histological change, which is based in particular on an overexpression of IgG4 and subsequent fibrosis.…
View article: Comparing Causal Discovery Methods using Synthetic and Real Data
Comparing Causal Discovery Methods using Synthetic and Real Data Open
<p>Unveiling causal structures, i.e., distinguishing cause from effect, from observational data plays a key role in climate science as well as in other fields like medicine or economics. Hence, a number of approaches has been develop…
View article: Active Learning for Deep Object Detection
Active Learning for Deep Object Detection Open
The great success that deep models have achieved in the past is mainly owed to large amounts of labeled training data. However, the acquisition of labeled data for new tasks aside from existing benchmarks is both challenging and costly. Ac…
View article: Active Learning for Deep Object Detection
Active Learning for Deep Object Detection Open
The great success that deep models have achieved in the past is mainly owed to large amounts of labeled training data. However, the acquisition of labeled data for new tasks aside from existing benchmarks is both challenging and costly. Ac…
View article: Keeping the Human in the Loop: Towards Automatic Visual Monitoring in Biodiversity Research
Keeping the Human in the Loop: Towards Automatic Visual Monitoring in Biodiversity Research Open
More and more methods in the area of biodiversity research grounds upon new opportunities arising from modern sensing devices that in principle make it possible to continuously record sensor data from the environment. However, these opport…
View article: Fast Learning and Prediction for Object Detection using Whitened CNN Features
Fast Learning and Prediction for Object Detection using Whitened CNN Features Open
We combine features extracted from pre-trained convolutional neural networks (CNNs) with the fast, linear Exemplar-LDA classifier to get the advantages of both: the high detection performance of CNNs, automatic feature engineering, fast mo…
View article: Active and Continuous Exploration with Deep Neural Networks and Expected\n Model Output Changes
Active and Continuous Exploration with Deep Neural Networks and Expected\n Model Output Changes Open
The demands on visual recognition systems do not end with the complexity\noffered by current large-scale image datasets, such as ImageNet. In\nconsequence, we need curious and continuously learning algorithms that actively\nacquire knowled…
View article: Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes
Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes Open
The demands on visual recognition systems do not end with the complexity offered by current large-scale image datasets, such as ImageNet. In consequence, we need curious and continuously learning algorithms that actively acquire knowledge …