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2,572 papers
A product-form queueing-network (PFQN) model with an approximation to capture the computation and communication dynamics of tree-structured task execution in a multi-tier MEC system is developed and results show that the proposed PFQN approximation provides accurate delay estimates.
We study random planar quadrangulations in which each block -- i.e., each simple (without multiple edges) component -- is assigned a weight $u$. We derive an explicit expression for the distance-dependent two-point function, defined as the generating function of such block-weighted maps with two marked edges at a fixed...
A computationally efficient stereo matching architecture, termed MCFNet, designed to minimize processing bottlenecks without compromising accuracy is introduced, highlighting its potential for practical multimedia systems such as autonomous driving and intelligent robotics.
This work presents a WebAssembly/Rust toolset with a geospatial data pipeline and efficient implementation of connectivity analysis, which has the potential to reduce backend operational complexity, resource requirements, and overall cost.
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ABSTRACT Reconfigurable optoelectronic image sensors capable of in‐sensor computing are promising for energy‐efficient edge visual perception. Self‐powered photovoltaic operation further reduces the power demand of image sensing and processing. However, it remains challenging to achieve a continuously gate‐tunable self...
An Enhanced Content-Based Image Retrieval Using Fusion of Feature Representation with Optimised Image Similarity Measures (CBIRFR-OISM) approach is proposed to effectively enhance the system’s capability to retrieve visually and contextually similar images.
Physical reservoir computing (PRC) offers a promising pathway for energy-efficient edge intelligence; however, existing micro-electromechanical systems (MEMS) implementations struggle to balance computational dimensionality with hardware complexity. Here, we introduce a parallel reservoir architecture realized within a...
A unified analytical framework is introduced that models inference latency, bandwidth, energy, computational complexity, throughput, and model compression, and is used to compare cloud versus edge execution.
This review synthesizes the current body of literature on AI-IoT integration in precision farming, covering the core enabling technologies — smart sensors, unmanned aerial vehicles, UAVs, geographic information systems, GIS, edge and cloud computing, and block chain-based traceability — and the layered architecture thr...
Simulation results show that the proposed strategy converges rapidly and consistently outperforms benchmark schemes in latency and energy efficiency, while providing stronger adaptability to human-machine collaborative quality inspection scenarios.
A persistent gap between technical performance and comparative, longitudinal, and distributionally assessed urban-service outcomes is identified and a persistent gap between technical performance and comparative, longitudinal, and distributionally assessed urban-service outcomes is identified.
It is argued that AI should augment rather than replace trained security personnel and that performance must be assessed using airport-specific measures such as detection probability, false-alarm burden, alert-to-intervention time, crowd-risk prediction, system availability and passenger-impact indicators.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
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