16 citations · 77 across the 23 of their papers we have counts for
7 papers · 1 filter
TinyAC: Bringing Autonomic Computing Principles to Resource-Constrained Systems
Wojciech Kalka, Ruitao Xue, Kamil Faber +4
Autonomic Computing (AC) is a promising approach for developing intelligent and adaptive self-management systems at the deep network edge. In this paper, we present the problems an…
Trustworthy Second-hand Marketplace for Built Environment
Stanly Wilson, Kwabena Adu-Duodu, Yinhao Li +6
The construction industry faces significant challenges regarding material waste and sustainable practices, necessitating innovative solutions that integrate automation, traceabilit…
Benchmarking of CPU-intensive Stream Data Processing in The Edge Computing Systems
Tomasz Szydlo, Viacheslav Horbanov, Devki Nandan Jha +3
Edge computing has emerged as a pivotal technology, offering significant advantages such as low latency, enhanced data security, and reduced reliance on centralized cloud infrastru…
D2Fusion: Dual-domain Fusion with Feature Superposition for Deepfake Detection
Xueqi Qiu, Xingyu Miao, Fan Wan +5
Deepfake detection is crucial for curbing the harm it causes to society. However, current Deepfake detection methods fail to thoroughly explore artifact information across differen…
FedSCA: Federated Tuning with Similarity-guided Collaborative Aggregation for Heterogeneous Medical Image Segmentation
Yumin Zhang, Yan Gao, Haoran Duan +4
Transformer-based foundation models (FMs) have recently demonstrated remarkable performance in medical image segmentation. However, scaling these models is challenging due to the l…
A Circular Construction Product Ontology for End-of-Life Decision-Making
Kwabena Adu-Duodu, Stanly Wilson, Yinhao Li +8
Efficient management of end-of-life (EoL) products is critical for advancing circularity in supply chains, particularly within the construction industry where EoL strategies are hi…
Laser: Efficient Language-Guided Segmentation in Neural Radiance Fields
Xingyu Miao, Haoran Duan, Yang Bai +5
In this work, we propose a method that leverages CLIP feature distillation, achieving efficient 3D segmentation through language guidance. Unlike previous methods that rely on mult…