ListarLCC - Contribuciones a congresos científicos por tema "Redes neuronales (Informática)"
Mostrando ítems 1-15 de 15
-
A generic LSTM neural network architecture to infer heterogeneous model transformations.
(2023)Models capture relevant properties of systems. During the models’ life-cycle, they are subjected to manipulations with different goals such as managing software evolution, performing analysis, increasing developers’ ... -
A novel continual learning approach for competitive neural networks
(2022)Continual learning tries to address the stability-plasticity dilemma to avoid catastrophic forgetting when dealing with non-stationary distributions. Prior works focused on supervised or reinforcement learning, but few ... -
An improved multi-objective genetic algorithm for the neural architecture search problem.
(2023)In recent years, there is a great interest in automating the process of searching for neural network topology. This problem is called Neural Architecture Search (NAS), which can be seen as a 3-gear mechanism: the search ... -
Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks
(Springer, 2018)The detection of red blood cells in blood samples can be crucial for the disease detection in its early stages. The use of image processing techniques can accelerate and improve the effectiveness and efficiency of this ... -
Comparación de marcos de trabajo de Aprendizaje Profundo para la detección de objetos
(2018-11-08)Muchas aplicaciones en visión por computador necesitan de sistemas de detección precisos y eficientes. Esta demanda coincide con el auge de la aplicación de técnicas de aprendizaje profundo en casi todos las áreas del ... -
Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras
(IEEE, 2018)Automatic video surveillance systems are usually designed to detect anomalous objects being present in a scene or behaving dangerously. In order to perform adequately, they must incorporate models able to achieve accurate ... -
Encoding generative adversarial networks for defense against image classification attacks
(2022)Image classification has undergone a revolution in recent years due to the high performance of new deep learning models. However, severe security issues may impact the performance of these systems. In particular, adversarial ... -
Foreground object detection enhancement by adaptive super resolution for video surveillance
(2019-09-16)Foreground object detection is a fundamental low level task in current video surveillance systems. It is usually accomplished by keeping a model of the background at each frame pixel. Many background learning algorithms ... -
Infering Air Quality from Traffic Data using Transferable Neural Network Models
(Springer, 2019-06)This work presents a neural network based model for inferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet legislative and policy ... -
Optimising traffic lights with metaheuristics: Reduction of car emissions and consumption
(IEEE, 2014-07)In last years, enhancing the vehicular traffic flow becomes a mandatory task to minimize the impact of polluting emissions and unsustainable fuel consumption in our cities. Smart Mobility optimisation emerges then, with ... -
Pneumonia Detection in Chest X-ray Images using Convolutional Neural Networks
(2022)Pneumonia is an infectious and deadly disease which strikes over millions of people. Usually, chest X-rays are used by radiotherapist to diagnose pneumonia. In this paper, a Computer- Aided Diagnosis (CAD) system for ... -
Solving the quadratic assignment problem by neural networks
(2013-10-30)The Quadratic Assignment Problem (QAP) was introduced by Koopmans and Beckmann in 1957 as a mathematical model for the location of a set of indivisible economical activities. This problem consists of allocating a set of ... -
Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks
(IEEE, 2018)Enhancing resolution is a permanent goal in magnetic resonance (MR) imaging, in order to keep improving diagnostic capability and registration methods. Super-resolution (SR) techniques are applied at the postprocessing ... -
Vehicle Classification in Traffic Environments Using the Growing Neural Gas
(Springer, 2017)Traffic monitoring is one of the most popular applications of automated video surveillance. Classification of the vehicles into types is important in order to provide the human traffic controllers with updated information ... -
Vehicle Type Detection by Convolutional Neural Networks
(Springer, 2017)In this work a new vehicle type detection procedure for traffic surveillance videos is proposed. A Convolutional Neural Network is integrated into a vehicle tracking system in order to accomplish this task. Solutions for ...