|
|
|
Cesar G. Pachon, Diego Renza and Dora Ballesteros
One of the strategies adopted to compress CNN models for image classification tasks is pruning, where some elements, channels or filters of the network are discarded. Typically, pruning methods present results in terms of model performance before and aft...
ver más
|
|
|
|
|
|
|
Adrian F. Chavarro, Diego Renza and Dora M. Ballesteros
Most of the world?s crops can be attacked by various diseases or pests, affecting their quality and productivity. In recent years, transfer learning with deep learning (DL) models has been used to detect diseases in maize, tomato, rice, and other crops. ...
ver más
|
|
|
|
|
|
|
Diego Renza and Dora Ballesteros
CNN models can have millions of parameters, which makes them unattractive for some applications that require fast inference times or small memory footprints. To overcome this problem, one alternative is to identify and remove weights that have a small im...
ver más
|
|
|
|
|
|
|
César G. Pachón, Dora M. Ballesteros and Diego Renza
Recently, some state-of-the-art works have used deep learning-based architectures, specifically convolutional neural networks (CNNs), for banknote recognition and counterfeit detection with promising results. However, it is not clear which design strateg...
ver más
|
|
|
|
|
|
|
Diego Renza, Jaime Andres Arango and Dora Maria Ballesteros
This paper addresses a problem in the field of audio forensics. With the aim of providing a solution that helps Chain of Custody (CoC) processes, we propose an integrity verification system that includes capture (mobile based), hash code calculation and ...
ver más
|
|
|
|