Results 21 to 30 of about 15,702 (241)
Edge Impulse: An MLOps Platform for Tiny Machine Learning
CoRR, 2022 Edge Impulse is a cloud-based machine learning operations (MLOps) platform for developing embedded and edge ML (TinyML) systems that can be deployed to a wide range of hardware targets. Current TinyML workflows are plagued by fragmented software stacks and heterogeneous deployment hardware, making ML model optimizations difficult and unportable.
Colby R. Banbury +15 more
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An 8-bit Single Perceptron Processing Unit for Tiny Machine Learning Applications
IEEE Access, 2023 We present a tiny MultiLayer Perceptron (MLP) accelerator named Single Perceptron Linear Vector Processor (SPLVP) that aims at extending the capabilities of limited resources MCUs, enabling inference time speedup and main CPU off-load.
Marco Crepaldi +2 more
doaj +1 more source
A review on TinyML: State-of-the-art and prospects
Journal of King Saud University: Computer and Information Sciences, 2022 Machine learning has become an indispensable part of the existing technological domain. Edge computing and Internet of Things (IoT) together presents a new opportunity to imply machine learning techniques at the resource constrained embedded devices at ...
Partha Pratim Ray
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Micromachines, 2022 Recently, the Internet of Things (IoT) has gained a lot of attention, since IoT devices are placed in various fields. Many of these devices are based on machine learning (ML) models, which render them intelligent and able to make decisions.
Norah N. Alajlan, Dina M. Ibrahim
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DeepEdge: A Novel Appliance Identification Edge Platform for Data Gathering, Capturing and Labeling
Sensors, 2022 With the development of the Internet of Things for smart grid, the requirement for appliance monitoring has become an important topic. The first and most important step in appliance monitoring is to identify the type of appliance.
Zilin Wang +5 more
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The synergy of complex event processing and tiny machine learning in industrial IoT [PDF]
Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems, 2021 Accepted by The 15th ACM International Conference on Distributed and Event-based Systems (DEBS ...
Haoyu Ren +2 more
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A Quantitative Review of Automated Neural Search and On-Device Learning for Tiny Devices
Chips, 2023 This paper presents a state-of-the-art review of different approaches for Neural Architecture Search targeting resource-constrained devices such as microcontrollers, as well as the implementations of on-device learning techniques for them.
Danilo Pietro Pau +2 more
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A Cost-Efficient FPGA-Based CNN-Transformer Using Neural ODE
IEEE AccessTransformer has been adopted to image recognition tasks and shown to outperform CNNs and RNNs while it suffers from high training cost and computational complexity.
Ikumi Okubo +2 more
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Custom Hardware Inference Accelerator for TensorFlow Lite for Microcontrollers
IEEE Access, 2022 In recent years, the need for the efficient deployment of Neural Networks (NN) on edge devices has been steadily increasing. However, the high computational demand required for Machine Learning (ML) inference on tiny microcontroller-based IoT devices ...
Erez Manor, Shlomo Greenberg
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Deep and Wide Tiny Machine Learning
, 2022 AbstractIn the last decades, on the one hand, Deep Learning (DL) has become state of the art in several domains, e.g., image classification, object detection, and natural language processing. On the other hand, pervasive technologies—Internet of Things (IoT) units, embedded systems, and Micro-Controller Units (MCUs)—ask for intelligent processing ...
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