of Machine Learning
at the Edge
Qeexo develops machine learning solutions that generate actionable insights from sensor data.
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First automated ML platform for an Arm Cortex-M0/M0+
Supporting a wide range of machine learning algorithms, Qeexo AutoML is designed for lightweight, Cortex-M0-to-M4-class processors, yielding ultra-low power consumption and latency.
Automatically Build Machine Learning
Solutions with Sensor Data
Why Qeexo AutoML?
Trending Articles
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FEATURED BLOG Sound Recognition with Qeexo AutoML
Introduction Sound Recognition is a technology based on traditional pattern recognition theories and signal analysis methods which is widely used in speech recognition, music recognition and many other research areas such as acoustical oceanography [1]. Generally, microphones are regarded as sufficient sensing modalities as input to machine learning methods within these fields. Microphones are capable […]
Zhongyu Ouyang and Dr. Geoffrey Newman 21 September 2020 -
PRESS Qeexo Adds Support for Arm’s Edge Processor
Qeexo, the “tinyML” specialist, said its AutoML platform now supports the smallest Cortex processors from Arm Ltd., making it the first vendor to automate machine learning on the Arm processor used for edge computing in sensors and...
Datanami 12 October 2020 -
PRESS Qeexo AutoML Enables Machine Learning on Arm Cortex-M0 and Cortex-M0+
First company to build an automated ML platform for the Arm Cortex-M0 and Cortex-M0+ processor MOUNTAIN VIEW, Calif. (PRWEB) September 09, 2020 Qeexo, developer of an automated machine learning (ML) platform that accelerates the deployment of tinyML...
Qeexo, Co. 09 September 2020 -
BLOG Inference Settings: Instance Length and Classification Interval
Qeexo AutoML enables machine learning application developers to customize inference settings based on their use-case. These parameters are critical for achieving the best live performance of models on the embedded target. In this article, we will...
Xun (Jared) Liu, Dr. Rajen Bhatt, and Dr. Geoffrey Newman
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