Harnessing Temporal Information for Efficient Edge AI

M Sponner, L Servadei, B Waschneck… - … Conference on Fog …, 2024 - ieeexplore.ieee.org
Deep Learning is becoming increasingly relevant in edge and Internet-of-Things
applications. However, deploying models on embedded devices is challenging due to their …

Temporal decisions: Leveraging temporal correlation for efficient decisions in early exit neural networks

M Sponner, L Servadei, B Waschneck, R Wille… - arxiv preprint arxiv …, 2024 - arxiv.org
Deep Learning is becoming increasingly relevant in Embedded and Internet-of-things
applications. However, deploying models on embedded devices poses a challenge due to …

Leveraging Temporal Patterns: Automated Augmentation to Create Temporal Early Exit Networks for Efficient Edge AI

M Sponner, L Servadei, B Waschneck, R Wille… - IEEE …, 2024 - ieeexplore.ieee.org
In embedded systems, efficient deep learning solutions are crucial to balance accuracy and
resource constraints. Early Exit Neural Networks offer a promising solution, but their manual …

[PDF][PDF] Innovative Techniques for Enhanced Data Analysis and Classification in Various Domains

I Chen, L Evans, A Mitchell, R Patel, E Walker… - Authorea …, 2023 - researchgate.net
The advancement of data analysis and classification is crucial for extracting valuable
insights from vast datasets across multiple domains. In this work, we present a suite of …

[PDF][PDF] Deep Learning Techniques for Efficient Multimodal Medical Data Analysis

Y Li, X Zhao, J Xu, H Wang, S Liu, L Chen - researchgate.net
Deep learning has revolutionized various fields, including medical data analysis, where
efficient handling of multimodal information is crucial. This research introduces advanced …

[PDF][PDF] Scalable Algorithms for Real-Time Change Point Detection in Streaming Covariates

J Liu, H Chen, L Li, M Zhang, X Wang, Z Yang - researchgate.net
Real-time change point detection in streaming covariates presents significant challenges
due to high-dimensional data and the dynamic nature of environments. Traditional detection …