6 datasets found

Mibench2 is a benchmark suite for embedded systems.

The dataset used in the paper is a collection of 89K static silent stores, each associated with 127 static program features.

The dataset used in this paper is a collection of state-of-the-art convolutional primitives for ARM Cortex-M microcontrollers.

The dataset is a SquashFS filesystem, which is a read-only filesystem often used to store the operating system of embedded devices.

The dataset is a dump of the Google Home's internal data, extracted by desoldering and dumping the flash memory.

This paper presents a scalable deep learning model called Agile Temporal Convolutional Network (ATCN) for high-accurate fast classification and time series prediction in...