Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Recognition of handwritten MNIST digits on low-memory 2 Kb RAM Arduino
  board using LogNNet reservoir neural network   The presented compact algorithm for recognizing handwritten digits of the
MNIST database, created on the LogNNet reservoir neural network, reaches the
recognition accuracy of 82%. The algorithm was tested on a low-memory Arduino
board with 2 Kb static RAM low-power microcontroller. The dependences of the
accuracy and time of image recognition on the number of neurons in the
reservoir have been investigated. The memory allocation demonstrates that the
algorithm stores all the necessary information in RAM without using additional
data storage, and operates with original images without preliminary processing.
The simple structure of the algorithm, with appropriate training, can be
adapted for wide practical application, for example, for creating mobile
biosensors for early diagnosis of adverse events in medicine. The study results
are important for the implementation of artificial intelligence on peripheral
constrained IoT devices and for edge computing.

21
The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th