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2,659 papers
The final geometry of a three-dimensional chip is commonly described by a combination of geometric parameters, including curl radius, pitch, and axis orientation. However, parameter combinations that are mathematically admissible do not necessarily correspond to material deformations that are kinematically realizable....
This study presents the design and experimental validation of an embedded edge artificial intelligence (AI) camera system for intelligent vision applications. The developed system integrates a multicore edge computing processor and a dedicated AI engine into a compact smart camera platform, enabling on-device image pro...
Building extraction from remote sensing images is a core task in urban planning and related applications. However, achieving high-precision building footprint extraction remains challenging due to complex building shapes and background noise. Existing mask-based methods produce raster masks with jagged edges, which gen...
The process of image denoising is very crucial in the field of image processing, since noise tends to adversely affect both the appearance and structure of images that are applied in different fields of study such as science and engineering. In this research paper, we present a new hybrid image-denoising scheme called...
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Abstract Future quantum networks will have to support different applications on shared infrastructure, like fidelity-critical Quantum Key Distribution (QKD) and latency-sensitive Distributed Quantum Computing (DQC). The existing approaches for entanglement routing either optimise for a single application, or rely on se...
Grid-cell indicators of urban morphology and microclimate for 67 cities (486,406 cells), computed from OpenStreetMap buildings and streets and from Sentinel-2 imagery. The record also includes a k-means typology of the cells (19 types) and an STL building model of one representative cell for each type, for use as CFD g...
EL-RAKHAWI HYPER-DIMENSIONAL COGNITIVE INTELLIGENCE MODEL (HDCI-DNSF)Author: Dr. Mohamed Kamal Arafa El-Rakhawi | DOI: 10.5281/zenodo.23370940 A paradigm-shifting patent disclosure redefining artificial intelligence from statistical approximation to deterministic cognitive resonance, overcoming hallucination, catastrop...
This chapter delves into the transformative synergy between artificial intelligence (AI) and smart contracts, positioning them as the next frontier in managing digital assets and virtual currencies. It introduces the core concepts, illustrating how AI injects adaptability into rigid blockchain-based contracts, enabling...
Traditional English teaching system has some problems, such as insufficient semantic understanding, low efficiency of personalized recommendation and high real-time interaction delay. This paper proposes an adaptive English teaching system based on AI. The system adopts a six layer microservice architecture, integratin...
Integrated sensing and communication (ISAC), semantic communication, and mobile edge computing (MEC) jointly create a high-dimensional, non-convex, and time-coupled resource allocation problem in sixth-generation (6G) networks that existing heuristics and deep reinforcement learning (DRL) methods solve either slowly or...
Learned resource allocators for sixth-generation edge networks usually treat operational limits as penalties and may return infeasible decisions. This paper studies energy minimization in multi-cell uplink non-orthogonal multiple access mobile edge computing networks. Treating inter-cell interference as a receiver-side...
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.
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.
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