Browsing CSEM Archive by Research Areas "Data & AI"
Now showing items 1-20 of 61
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A Reliable Approach for Pixel-Level Classification of Land usage from Spatio-Temporal Images
(2019)The ongoing advancements in deep learning, and exemplary results obtained for different problems using spatio-temporal satellite images, have made deep neural networks quite popular for analysing Earth Observation data. ... -
Adaptation of MobileNetV2 for Face Detection on Ultra-Low Power Platform
(2022-06)Designing Deep Neural Networks (DNNs) running on edge hardware remains a challenge. Standard designs have been adopted by the community to facilitate the deployment of Neural Network models. However, not much emphasis is ... -
Artificial Intelligence for Hospital Health Care: Application Cases and Answers to Challenges in European Hospitals
(2021-07-29)The development and implementation of artificial intelligence (AI) applications in health care contexts is a concurrent research and management question. Especially for hospitals, the expectations regarding improved ... -
Benchmarking Neuromorphic Computing for Inference
(2022-06)In the last decade, there has been significant progress in the IoT domain due to the advances in the accuracy of neural networks and the industrialization of efficient neural network accelerator ASICs. However, intelligent ... -
Collaborative Privacy-Preserving Decision Tree Learning
(2020-11-03)Building robust predictive machine learning (ML) models requires access to large datasets. Such datasets can be built by aggregating data held by multiple data providers. An example would be medical datasets, whereby ... -
A Construction Kit for Efficient Low Power Neural Network Accelerator Designs
(2022-09)Implementing embedded neural network processing at the edge requires efficient hardware acceleration that combines high computational throughput with low power consumption. Driven by the rapid evolution of network architectures ... -
Correlation Sketching for Ordered Data
(2017)Methods based on order statistics are often used in finance, quality control, data and signal processing, especially when signals of interest are immersed in impulsive noise. These allow to include rank information by ... -
Data Generation for Deep Learning
(2022-01-25)Big Data ist in aller Munde. Häufig sind allerdings gerade die Daten, die einen Mehrwert bringen nur aufwändig zu erhalten. Dazu kommt, dass Daten alleine meistens nicht ausreichen sondern eine Annotierung derer unerlässlich ... -
Deep Learning für die Industrie: Oder – Wie kommen Fledermäuse in die Produktion?
(2022-06-08)AI setzt sich immer stärker im Alltag durch: Übersetzungsprogramme, lustige Fotofilter auf dem Handy oder Fahrassistenzen im Auto. Nun steht der grosse Durchbruch in der produzierenden Industrie an. Perfekte Qualität und ... -
Deep Semantic Segmentation using NIR as extra physical information
(2019)Deep neural networks for semantic segmentation are most often trained with RGB color images, which encode the radiation visible to the human eyes. In this paper, we study if additional physical scene information, specifically ... -
Deepfake in the lab
(2022-06-07)Beyond robotics: automation with AI From visual inspection to predictive quality Synthetic data generation: the breakthrough for AI in the lab -
DeepFake for Life Sciences
(2022-05-16)Spheroids are three-dimensional cellular aggregates and one of the most common and versatile way to culture cells in 3D. In order to scale laboratory tests, automated processes are needed, including robust classification. ... -
Deploying a Convolutional Neural Network on Edge MCU and Neuromorphic Hardware Platforms
(2022-06)The rapid development of embedded technologies in recent decades has led to the advent of dedicated inference platforms for deep learning. However, unlike development libraries for the algorithms, hardware deployment is ...