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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Rodríguez Carmona, Esperanza
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Computer Science & IT Engineering

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Deep learning architectures for location and identification in storage systems Espitia Cubillos, Anny Astrid; Jimenez Moreno, Robinson; Rodríguez Carmona, Esperanza
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i1.pp592-601

Abstract

This document exposes the application of two deep learning models based on ResNet-18 architectures, intended for the location and identification of products in storage areas. One model obeys a tree structure and the other a structure under an ouroboron cycle. The performance of both models is evaluated using the metrics of training time, processing time and level of learning precision, which allows recommendations to be made regarding which one should be used for order preparation purposes, based on multilevel feature extraction. The total training time of the first model is 34.65 minutes and the second 40.43 minutes. The analysis of results allowed the detection parameters to be adjusted, finally with the refined models, through confusion matrices, precision results greater than 90% and processing times are obtained, which for model 1 is 6.8565 seconds and for model 2 is 4.884 seconds. For practical purposes, training times are not relevant, as are the precision and processing times for selecting the most convenient model according to the end user's objectives.
Interactive communication human-robot interface for reduced mobility people assistance Jiménez Moreno, Robinson; Espitia Cubillos, Anny Astrid; Rodríguez Carmona, Esperanza
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i2.pp917-924

Abstract

Communication between a robot and its user is essential for the execution of tasks, even more so in a scenario where the robot is designed to assist people with reduced mobility. This document presents the evaluation of a conversation script between a human user and a robot for assistance using pre-recorded responses, for this a methodology with three phases was proposed and applied: establishment of the training scheme of a convolutional network that allows recognize user's words for execution of tasks by the robot, generation of dialogue between the user and possible interactions with the assistive robot and finally, the measurement of perception of interface users. Results show a high level of accuracy with words selected to command the robot, using a convolutional neural network, with an audio input discriminated in its components mel frequency cepstral coefficients (MFCCs) and command sets of male and female voices. It was possible to establish a dialogue model with three scenes to recognize the residential environment, rename spaces and execute action commands to move elements. It is concluded the designed instrument is reliable and the perception of proposed interactive communication interface is good in terms of usability (effectiveness, efficiency, and user satisfaction).
Co-Authors Espitia Cubillos, Anny Astrid Jimenez Moreno, Robinson