Although optimizing deep neural networks is becoming crucial for deploying the networks on
edge AI devices, it faces increasing challenges due to scarce hardware resources in modern …

The aim of this paper is to show the possible application of Tiny-ML family neural networks
to social robots for face recognition. Social robotics is a constantly developing field that …

Detecting defects on surfaces is a crucial challenge in the steel industry. Various object
detection models, including one-stage and two-stage approaches, have been developed to …

Traditional video analytics are typically performed on a single node having limited
processing power and vertical scalability, resulting in a lack of real-time performance and …

Widespread use of highly accurate and trustworthy deep learning architectures is becoming
a noticeable trend in the industry. Model accuracy and inferencing performance traditionally …

This thesis presents an automatic forklift approach for lifting and handling pallets. The
project more specifically develops a solution for autonomous object detection and pose …

Deep learning (DL) has proven to be a significant solution for analyzing complex datasets
such as images, videos, text, and speech. Convolutional neural networks (CNN) have …