Name
Title | ||
|---|---|---|
AI Pipeline - bringing AI to you. End-to-end integration of data, algorithms and deployment tools. |
Abstract | ||
|---|---|---|
Next generation of embedded Information and Communication Technology (ICT) systems are interconnected collaborative intelligent systems able to perform autonomous tasks. Training and deployment of such systems on Edge devices however require a fine-grained integration of data and tools to achieve high accuracy and overcome functional and non-functional requirements. In this work, we present a modular AI pipeline as an integrating framework to bring data, algorithms and deployment tools together. By these means, we are able to interconnect the different entities or stages of particular systems and provide an end-to-end development of AI products. We demonstrate the effectiveness of the AI pipeline by solving an Automatic Speech Recognition challenge and we show that all the steps leading to an end-to-end development for Key-word Spotting tasks: importing, partitioning and pre-processing of speech data, training of different neural network architectures and their deployment on heterogeneous embedded platforms. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Learning | Journal |
Volume | Citations | PageRank |
abs/1901.05049 | 1 | 0.35 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel de Prado | 1 | 1 | 0.35 |
| Jing Su | 2 | 19 | 5.22 |
| Rozenn Dahyot | 3 | 340 | 32.62 |
| Rabia Saeed | 4 | 1 | 0.69 |
| Lorenzo Keller | 5 | 1 | 0.35 |
| Noelia Vállez | 6 | 25 | 8.57 |