Raquel Lazcano

Orcid: 0000-0002-2645-6749

According to our database1, Raquel Lazcano authored at least 25 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Monetizing Currency Pair Sentiments through LLM Explainability.
CoRR, 2024

Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons.
CoRR, 2024

In-Vivo Hyperspectral Human Brain Image Database for Brain Cancer Detection.
CoRR, 2024

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations.
CoRR, 2024

2023

2022
Energy Consumption and Runtime Performance Optimizations Applied to Hyperspectral Imaging Cancer Detection.
Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

2020
Runtime multi-versioning and specialization inside a memoized speculative loop optimizer.
Proceedings of the CC '20: 29th International Conference on Compiler Construction, 2020

2019
Adaptation of an Iterative PCA to a Manycore Architecture for Hyperspectral Image Processing.
J. Signal Process. Syst., 2019

PAPIFY: Automatic Instrumentation and Monitoring of Dynamic Dataflow Applications Based on PAPI.
IEEE Access, 2019

Parallel Implementations Assessment of a Spatial-Spectral Classifier for Hyperspectral Clinical Applications.
IEEE Access, 2019

In-Vivo Hyperspectral Human Brain Image Database for Brain Cancer Detection.
IEEE Access, 2019

Hardware/Software Self-adaptation in CPS: The CERBERO Project Approach.
Proceedings of the Embedded Computer Systems: Architectures, Modeling, and Simulation, 2019

Characterizing Hyperspectral Data Layouts: Performance and Energy Efficiency in Embedded GPUs for PCA-based Dimensionality Reduction.
Proceedings of the XXXIV Conference on Design of Circuits and Integrated Systems, 2019

2018
Accelerating the K-Nearest Neighbors Filtering Algorithm to Optimize the Real-Time Classification of Human Brain Tumor in Hyperspectral Images.
Sensors, 2018

An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation.
Sensors, 2018

Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons.
Remote. Sens., 2018

Automatic instrumentation of dataflow applications using PAPI.
Proceedings of the 15th ACM International Conference on Computing Frontiers, 2018

2017
SVM-based real-time hyperspectral image classifier on a manycore architecture.
J. Syst. Archit., 2017

Porting a PCA-based hyperspectral image dimensionality reduction algorithm for brain cancer detection on a manycore architecture.
J. Syst. Archit., 2017

High-level design using Intel FPGA OpenCL: A hyperspectral imaging spatial-spectral classifier.
Proceedings of the 12th International Symposium on Reconfigurable Communication-centric Systems-on-Chip, 2017

Energy consumption characterization of a Massively Parallel Processor Array (MPPA) platform running a hyperspectral SVM classifier.
Proceedings of the 2017 Conference on Design and Architectures for Signal and Image Processing, 2017

Parallel implementation of an iterative PCA algorithm for hyperspectral images on a manycore platform.
Proceedings of the 2017 Conference on Design and Architectures for Signal and Image Processing, 2017

HELICoiD: interdisciplinary and collaborative project for real-time brain cancer detection: Invited Paper.
Proceedings of the Computing Frontiers Conference, 2017

2016
Demo: HELICoiD tool demonstrator for real-time brain cancer detection.
Proceedings of the 2016 Conference on Design and Architectures for Signal and Image Processing (DASIP), 2016

Hyperspectral image classification using a parallel implementation of the linear SVM on a Massively Parallel Processor Array (MPPA) platform.
Proceedings of the 2016 Conference on Design and Architectures for Signal and Image Processing (DASIP), 2016


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