Listar por tema "Deep neural networks"
Mostrando ítems 1-20 de 36
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360-Attack: Distortion-Aware Perturbations from Perspective-Views
(2022)The application of deep neural networks (DNNs) on 360-degree images has achieved remarkable progress in the recent years. However, DNNs have been demonstrated to be vulnerable to well-crafted adversarial examples, which ... -
An AI-based Prediction-as-a-Service Model for Estimating Machine Bearing Health Status in Industry 4.0 5G Applications
(2021)Intelligent Machine Condition Monitoring (MCM) and Prediction for machine bearings is very important for efficient Industrial 5G applications. Common fault diagnosis and other classification methods usually extract time ... -
Anomaly detection via blockchained deep learning smart contracts in industry 4.0
(2020)The complexity of threats in the ever-changing environment of modern industry is constantly increasing. At the same time, traditional security systems fail to detect serious threats of increasing depth and duration. ... -
Application of deep learning and chaos theory for load forecasting in Greece
(2021)In this paper, a novel combination of deep learning recurrent neural network and Lyapunov time is proposed to forecast the consumption of electricity load, in Greece, in normal/abrupt change value areas. Our method verifies ... -
Artificial intelligence implementations on the blockchain. Use cases and future applications
(2019)An exemplary paradigm of how an AI can be a disruptive technological paragon via the utilization of blockchain comes straight from the world of deep learning. Data scientists have long struggled to maintain the quality of ... -
Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks
(2017)One of the most important policy reforms for the European Union (EU) agriculture was the implementation of the Agenda 2000, which establishes a new framework for subsidies management, decoupled from both crop and animal ... -
Attention-Enhanced Sensorimotor Object Recognition
(2018)Sensorimotor learning, namely the process of understanding the physical world by combining visual and motor information, has been recently investigated, achieving promising results for the task of 2D/3D object recognition. ... -
A Convolutional Neural Network-based explainable classification method of SPECT myocardial perfusion images in nuclear cardiology
(2022)This study targets on the development of an explainable Convolutional Neural Network (CNN) pipeline in the form of a handcrafted CNN to identify patients' coronary artery disease status (normal, ischemia or infarction). ... -
Convolutional Variational Autoencoders for Image Clustering
(2021)The problem of data clustering is one of the most fundamental and well studied problems of unsupervised learning. Image clustering, refers to one of the most challenging specifications of clustering, concerning image data. ... -
Credit card fraud detection using a deep learning multistage model
(2022)The banking sector is on the eve of a serious transformation and the thrust behind it is artificial intelligence (AI). Novel AI applications have been already proposed to deal with challenges in the areas of credit scoring, ... -
Deep Endoscopic Visual Measurements
(2019)Robotic endoscopic systems offer a minimally invasive approach to the examination of internal body structures, and their application is rapidly extending to cover the increasing needs for accurate therapeutic interventions. ... -
Deep learning in water resources management: The case study of Kastoria lake in Greece
(2021)The effects of climate change on water resources management have drawn worldwide attention. Water quality predictions that are both reliable and precise are critical for an effective water resources management. Although ... -
Deep sensorimotor learning for RGB-D object recognition
(2020)Research findings in cognitive neuroscience establish that humans, early on, develop their understanding of real-world objects by observing others interact with them or by performing active exploration and physical ... -
Design Space Exploration of a Sparse MobileNetV2 Using High-Level Synthesis and Sparse Matrix Techniques on FPGAs
(2022)Convolution Neural Networks (CNNs) are gaining ground in deep learning and Artificial Intelligence (AI) domains, and they can benefit from rapid prototyping in order to produce efficient and low-power hardware designs. The ... -
Detecting audio-visual synchrony using deep neural networks
(2015)In this paper, we address the problem of automatically detecting whether the audio and visual speech modalities in frontal pose videos are synchronous or not. This is of interest in a wide range of applications, for example ... -
Development of Convolutional Neural Networkbased models for bone metastasis classification in nuclear medicine
(2020)Focusing on prostate cancer patients, this research paper addresses the problem of bone metastasis diagnosis, investigating the capabilities of convolutional neural networks (CNN) and transfer learning. Considering the ... -
Early Fusion of Visual Representations of Skeletal Data for Human Activity Recognition
(2022)In this work we present an approach for human activity recognition which is based on skeletal motion, i.e., the motion of skeletal joints in the 3D space. More specifically, we propose the use of 4 well-known image ... -
ENORASI Assistive Computer Vision-based System for the Visually Impaired: A User Evaluation Study
(2022)Visual impairment affects a significantly large number of individuals and in many cases it may disturb their daily life. This study presents a novel prototype wearable device which aims to assist them in tasks such as ... -
Error Compensation Enhanced Day-Ahead Electricity Price Forecasting
(2022)The evolution of electricity markets has led to increasingly complex energy trading dynamics and the integration of renewable energy sources as well as the influence of several external market factors contributed towards ... -
An Event-triggered Visual Servoing Predictive Control Strategy for the Surveillance of Contour-based Areas using Multirotor Aerial Vehicles
(2022)In this paper, an Event-triggered Image-based Visual Servoing Nonlinear Model Predictive Controller (ET-IBVS-NMPC) for multirotor aerial vehicles is presented. The proposed scheme is developed for the autonomous surveillance ...