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2,919 papers
Processing data directly at edge nodes reduces latency and enhances data privacy and security, but the lack of advanced cooling on these devices makes them unsuitable for sustained AI training, leading to overheating and accelerated hardware degradation. This paper is motivated by the observation that edge data intensi...
Aiming at the problems such as the imbalance between accuracy and efficiency, insufficient adaptability of multi-scale defects and limited inference resources in the deployment of design material defect detection at the edge end, this paper proposes a lightweight detection method based on edge AI. In the training stage...
Background Delayed right-sided traumatic diaphragmatic hernia (TDH) may be overlooked during polytrauma assessment because concomitant injuries dominate attention and the liver can obscure diaphragmatic discontinuity. Subsequent respiratory and gastrointestinal symptoms may remain nonspecific until obstruction or visce...
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This study highlights HDTs as a paradigm shift with the potential to revolutionize healthcare delivery, improve patient outcomes, and enable a more proactive, data-driven model of care.
Experimental results demonstrate that the proposed PUF-based authentication framework achieves high resistance to common attacks, such as eavesdropping, replay, and machine learning-based attacks while adhering to the low-latency requirements of edge networks.
The experimental results indicate significant reductions in computational and communication overhead, making the proposed technique ideal for UAV-enabled edge intelligent IoT environments and confirming its effectiveness as a secure and efficient cryptographic foundation for next-generation UAV swarm communication.
LiteDANN, a lightweight semi-supervised domain-adaptation framework for cross-condition bearing fault diagnosis, provides a practical basis for real-time bearing diagnosis on resource-constrained edge platforms.
Our research topic has inspired studies on new results on lightweight computer vision (CV) models and edge deployment strategies for crop production. With the proliferation of unmanned aerial vehicles (UAVs), autonomous harvesters, and Internet-of-Things (IoT) devices in agriculture, the demand for efficient, accurate,...
A large-model-driven vision-language cross-modal semantic SLAM and heuristic topology planning architecture that achieves zero-sample 3D geometric matching of open vocabularies through a deep dual-stream feature network and designs a semantic confidence-weighted core optimization mechanism to effectively suppress multi...
This review highlights the critical threats, architectural considerations, and strategic measures necessary to secure cloud and IoT infrastructures, enabling organizations to leverage these technologies safely and effectively.
Neutron computed tomography (nCT) was acquired from a corner of each sample to guarantee that a distinct edge remained visible during the full rotation.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
Education Innovation
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
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