Πλοήγηση ανά Θέμα "Neural Networks, Computer"
Αποτελέσματα 1-12 από 12
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Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application
(2020)Bone metastasis is one of the most frequent diseases in prostate cancer; scintigraphy imaging is particularly important for the clinical diagnosis of bone metastasis. Up to date, minimal research has been conducted regarding ... -
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 exploration for SPECT MPI polar map images classification in coronary artery disease
(2022)Objective: The exploration and the implementation of a deep learning method using a state-of-the-art convolutional neural network for the classification of polar maps represent myocardial perfusion for the detection of ... -
DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data
(2022)Background: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE ... -
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 ... -
Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy
(2020)Objective: The main aim of this work is to build a robust Convolutional Neural Network (CNN) algorithm that efficiently and quickly classifies bone scintigraphy images, by determining the presence or absence of prostate ... -
Diagnosis of Induced Resistance State in Tomato Using Artificial Neural Network Models Based on Supervised Self-Organizing Maps and Fluorescence Kinetics
(2022)The aim of this study was to develop three supervised self-organizing map (SOM) models for the automatic recognition of a systemic resistance state in plants after application of a resistance inducer. The pathosystem ... -
Differentiation between subchondral insufficiency fractures and advanced osteoarthritis of the knee using transfer learning and an ensemble of convolutional neural networks
(2022)Purpose: Subchondral insufficiency fractures (SIF) and advanced osteoarthritis (OA) of the knee are usually seen in conjunction with bone marrow lesions (BMLs) and their differentiation may pose a significant diagnostic ... -
Exploring social determinants of municipal solid waste management: survey processing with fuzzy logic and self-organized maps
(2019)In the present study, the establishment of decision-making criteria and a novel and robust interdisciplinary approach for systematically characterizing effects of uncertainties in social determinants of municipal solid ... -
Machine learning for rhabdomyosarcoma histopathology
(2022)Correctly diagnosing a rare childhood cancer such as sarcoma can be critical to assigning the correct treatment regimen. With a finite number of pathologists worldwide specializing in pediatric/young adult sarcoma ... -
Multi-branch Convolutional Neural Network for Identification of Small Non-coding RNA genomic loci
(2020)Genomic regions that encode small RNA genes exhibit characteristic patterns in their sequence, secondary structure, and evolutionary conservation. Convolutional Neural Networks are a family of algorithms that can classify ... -
Network stiffness: A new topological property in complex networks
(2019)Aiming at serving the interdisciplinary demand in network science, this paper introduces a new concept for complex networks, named network stiffness, which is extracted from structural engineering by assuming that a complex ...