We tackle automatic meter reading (AMR) by leveraging the high capability of convolutional
neural networks (CNNs). We design a two-stage approach that employs the Fast-YOLO …

Smart meters enable remote and automatic electricity, water and gas consumption reading
and are being widely deployed in developed countries. Nonetheless, there is still a huge …

Existing approaches for image-based Automatic Meter Reading (AMR) have been evaluated
on images captured in well-controlled scenarios. However, real-world meter reading …

Many tasks that require a large workforce are automated. In many areas of the world, the
consumption of utilities, such as electricity, gas and water, is monitored by meters that need …

With the growing demand for water resources, the need for monitoring has become a
necessity for rational and sustainable use of this resource. Water meter data collection is an …

Gas serves as one of the most indispensable energy sources for industrial production and
household life. In order to improve the gas utilization efficiency, smart gas meters for the …

With the development of Industry 4.0, although some smart meters have appeared on the
market, traditional mechanical meters are still widely used due to their long-standing …

In this paper we present a segmentation-free system for reading text in natural scenes. A
CNN architecture is trained in an end-to-end manner, and is able to directly output readings …

The replacement of analog meters with smart meters is costly, laborious, and far from
complete in develo** countries. The Energy Company of Paraná (Copel)(Brazil) performs …

Nowadays, the meter reading is detached into two parts: 1) image collection and 2) image
recognition. Most previous researchers perceived meter reading as an image classification …