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3,051 papers
The proposed framework provides an interpretable geometry-based approach for extending conventional obstacle detection toward railway risk-aware perception, showing potential for intelligent railway inspection, early warning, and safety-oriented operation and maintenance.
TripleBound is proposed, a hybrid framework for automated monolith-to-microservices decomposition that augments a heterogeneous graph neural network with weakly supervised triplet constraints derived from parser-inferred service groups based on package structure, naming conventions, and code location.
A deep learning-based forensic framework for real-time detection of suspicious human activity in CCTV videos, trained without relying on any external sensors is proposed, and incorporates anonymization of personal identities and local edge-based processing to prevent raw data exposure.
We implement a second-order accurate constrained transport (CT) magnetohydrodynamics (MHD) module with first-order flux correction in the open-source, adaptive mesh refinement (AMR), GPU-accelerated code quokka, supporting both ideal and resistive (constant Ohmic) regimes. For computing and averaging the electromotive...
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We compute the energy gained by accretion onto a compact star due to matter falling from the inner edge of a thin accretion disk. We employ a controlled slow-rotation expansion based on the Hartle-Thorne metric and find that in neutron stars in general only leading order rotational corrections to the metric, describing...
Digital function-oriented communication is presented, in which finite-alphabet symbol representations and receiver decisions are jointly designed so that multiple-access superposition encodes the desired function without recovering individual inputs.
The first prototype of a 5G-connected mobile edge computing (MEC)-enabled semi-autonomous prosthetic hand is presented, which streams RGB-D images to an edge server for real-time grasp planning and establishes 5G edge-offloading as a practical path to deploying compute-intensive prosthesis control.
This paper synthesizes reported evidence on ZTA across three research questions: effectiveness relative to perimeter models, the implementation challenges enterprises face, and the security contribution of individual components.
Split federated learning (SFL) is renowned for its low computational overhead, extremely suitable for resource-constrained edge computing scenarios while inheriting privacy-preserving characteristics from federated learning (FL). In this framework, clients employ lightweight models to process private data locally and t...
The proposed IR-AGN model exhibits a higher mean Average Precision (mAP) of 95.19% on the Revisited Paris (RParis) dataset, when compared with the existing Multi-Layer Orientation Histogram (MLOH) model.
The results show that a sub-6 GHz anchor with selective high-band duplication provides a good trade-off between latency, reliability and resource consumption.
Quantumer, a hybrid TinyML--quantum framework that integrates multi-scale dilated convolutions and scaled dot-product attention within a lightweight transformer architecture, employing a two-stage transfer learning pipeline from Quantum Pre-Training (Quantumer-Q) to Classical Fine-Tuning (Quantumer-C).
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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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.
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