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Deep Learning eredu batean oinarritutako irudien analisi eta azterketaren prototipo orokorgarri baten garapena: Nvidia Jetson TX1 plataforman inplementatuta
(2018-10-15)[ES] En este proyecto se ha trabajado con diferentes métodos utilizados en visión por computador con el objetivo de usarlos para la clasificación de imágenes. Para ello, se ha llevado a cabo un pre-procesado de imágenes ... -
Deep Learning for Inverting Borehole Resistivity Measurements.
(2022-11-25)El subsuelo terrestre está formado por diferentes materiales, principalmente por rocas porosas que posiblemente contienen minerales y están rellenas de agua salada y/o hidrocarburos. Por lo general, las formaciones que ... -
Deep learning for near-infrared spectral data modelling: Hypes and benefits
; ; ; ; Amigo Rubio, José Manuel
; ; ; ; ; ; (Elsevier, 2022-12)
Deep learning (DL) is emerging as a new tool to model spectral data acquired in analytical experiments. Although applications are flourishing, there is also much interest currently observed in the scientific community on ... -
Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions
Muhammad, Khan; Ullah, Amin; Lloret, Jaime; Del Ser Lorente, Javier; C. de Albuquerque, Victor Hugo (IEEE, 2021-07)
Advances in information and signal processing technologies have a significant impact on autonomous driving (AD), improving driving safety while minimizing the efforts of human drivers with the help of advanced artificial ... -
Deep learning for semantic parsing
(2020-12-04)This is the memory of an exploratory research project on techniques for reasoning on text with Deep Learning (DL). To study reasoning we focus on the problem of Natural Language Question-Understanding (NLQU), and in ... -
Deep learning for understanding multilabel imbalanced Chest X-ray datasets
; ; ; Del Ser Lorente, Javier; (Elsevier, 2023-07)
Over the last few years, convolutional neural networks (CNNs) have dominated the field of computer vision thanks to their ability to extract features and their outstanding performance in classification problems, for example ... -
Deep Learning para Microscopía de Superresolución
(2020-12-04)El problema principal que este trabajo anual ha solucionado ha sido el aumento artificialde la resolución de imágenes procedentes de microscopios electrónicos. Los centros deinvestigación biomédica suelen contar con un ... -
Deep learning review and its applications
(2015-10-08)Deep neural networks have recently gained popularity for improv- ing state-of-the-art machine learning algorithms in diverse areas such as speech recognition, computer vision and bioinformatics. Convolutional networks ... -
Deep Learning with Discriminative Margin Loss for Cross-Domain Consumer-to-Shop Clothes Retrieval
Alirezazadeh, Pendar; ; Moujahid, Abdelmalik (MDPI, 2022-03-30)
Consumer-to-shop clothes retrieval refers to the problem of matching photos taken by customers with their counterparts in the shop. Due to some problems, such as a large number of clothing categories, different appearances ... -
Deep Learning-Based Feature Extraction of Acoustic Emission Signals for Monitoring Wear of Grinding Wheels
; ; Sánchez Galíndez, José Antonio; ; (MDPI, 2022-09-13)
Tool wear monitoring is a critical issue in advanced manufacturing systems. In the search for sensing devices that can provide information about the grinding process, Acoustic Emission (AE) appears to be a promising ... -
Deep Learning-eko metodologia eta tresnak Data Science-an
(2020-01-16)[EUS] Testuen klasifikazioa testu jakin bat aurretik definituriko multzo finitu batean sailkatzeko zeregina da. Honek dokumentuen generoen identifikazioan, spam filtroetan... aplikazioak izanez. Lan honen helburua testuen ... -
Deep neural networks and data augmentationfor semantic labelling in a dialogue corpus
(2020-12-04)El presente proyecto estudia y aplica técnicas de Deep Neural Networks y Data Augmentation para el etiquetado semántico en un corpus de diálogo, todo ello en el ámbito del Sentiment Analysis. El objetivo principal es ... -
Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest
; ; ; Picón Ruiz, Artzai; Alonso González, Erik ; ; (MDPI, 2019-03-21)
The automatic detection of pulse during out-of-hospital cardiac arrest (OHCA) is necessary for the early recognition of the arrest and the detection of return of spontaneous circulation (end of the arrest). The only signal ... -
Deep Reinforcement Learning techniques for dynamic task offloading in the 5G edge-cloud continuum
; ; ; Perfecto del Amo, Cristina Begoña (Springer, 2024-05-03)
The integration of new Internet of Things (IoT) applications and services heavily relies on task offloading to external devices due to the constrained computing and battery resources of IoT devices. Up to now, Cloud Computing ... -
Deep transfer learning-based gaze tracking for behavioral activity recognition
(Elsevier, 2022-08)Computational Ethology studies focused on human beings is usually referred as Human Activity Recognition (HAR). Specifically, this paper belongs to a line of work on the identification of broad cognitive activities that ... -
Deep-sea benthic response to rapid climatic oscillations of the last glacial cycle in the SE Bay of Biscay
Rodríguez Lázaro, Julio Manuel; ; ; ; (Elsevier, 2017-06-09)
Paleoclimatic evolution of the last 140 ka (Marine Isotopic Stages MIS 1 to MIS 5) in the South Bay of Biscay has been studied by considering microfossil changes in sediment samples of deep core PP10-17. This core was ... -
Deep-sea paleoenvironmental evolution in the mid-Cretaceous of the Basque Pyrenees based on microfaunal analysis (Armintza section)
; ; ; Rodríguez Lázaro, Julio Manuel (Elsevier, 2023-05)
The mid-Cretaceous Black Flysch Group and Plentzia Formation constitute two key lithostratigraphic units in the evolution of the Pyrenean rift system but many of their paleoenvironmental characteristics are poorly known. ... -
Deepfakes on Twitter: Which Actors Control Their Spread?
Pérez Dasilva, Jesús Angel; ; (Cogitatio, 2021-03-03)
The term deepfake was first used in a Reddit post in 2017 to refer to videos manipulated using artificial intelligence techniques and since then it is becoming easier to create such fake videos. A recent investigation by ... -
Defect and structural imperfection effects on the electronic properties of BiTeI surfaces
(IOP Publishing, 2014-07-24)The surface electronic structure of the narrow-gap seminconductor BiTeI exhibits a large Rashba-splitting which strongly depends on the surface termination. Here we report on a detailed investigation of the surface morphology ... -
Defective pronouns in the history of Russian: null subjects and object clitics
(University of Nova Gorica, 2023-12-24)In this paper, I present a unified account for the change in referential null subjects and accusative clitics in Russian. Clitics and null subjects are minimal defective pronouns. In Old Russian, long verb movement was the ...