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ENTITY Andrea Mattia Garavagno

Andrea Mattia Garavagno

PulseAugur coverage of Andrea Mattia Garavagno — every cluster mentioning Andrea Mattia Garavagno across labs, papers, and developer communities, ranked by signal.

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RECENT · PAGE 1/1 · 6 TOTAL
  1. TOOL · CL_156315 ·

    New framework enables in-sensor AI for bearing fault diagnosis

    Researchers have developed BearingNAS, a Hardware-Aware Neural Architecture Search (HW-NAS) framework that enables intelligent fault diagnosis directly on sensor hardware. This framework is designed to operate within ex…

  2. TOOL · CL_109915 ·

    On-device NAS optimizes neural networks for real-time data analysis

    Researchers have developed a novel on-device Neural Architecture Search (NAS) method designed for near-sensor computing. This approach allows for the optimization of small neural networks directly on deployment devices,…

  3. RESEARCH · CL_99571 ·

    New method tackles data scarcity in AI fault diagnosis systems

    Researchers have developed a novel approach to designing Intelligent Fault Diagnosis Systems (IFDS) that addresses the challenge of limited labeled data. The method utilizes Deep Transfer Learning (DTL) by employing a p…

  4. TOOL · CL_96280 ·

    ColabNAS offers affordable HW NAS for lightweight CNNs

    Researchers have developed ColabNAS, an accessible hardware-aware neural architecture search (HW NAS) technique designed to create lightweight, task-specific convolutional neural networks (CNNs). This method, inspired b…

  5. TOOL · CL_96245 ·

    New method enables edge AI for privacy-sensitive IoT applications

    A new paper introduces a method for designing neural networks directly on IoT gateways, enabling edge-based machine learning for privacy-sensitive applications. This approach allows for the creation of custom, hardware-…

  6. RESEARCH · CL_93228 ·

    New NAS methods target efficiency and embedded devices · 4 sources tracked

    Researchers have developed new methods for neural architecture search (NAS) that aim to be more efficient and resource-conscious. One approach, InTrain, introduces a unified theoretical proxy for trainability by analyzi…