|
|
|
|
|
Huanhuan Zhang and Yufei Qie
Deep learning (DL) has made significant strides in medical imaging. This review article presents an in-depth analysis of DL applications in medical imaging, focusing on the challenges, methods, and future perspectives. We discuss the impact of DL on the ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Diego Mellado, Carolina Saavedra, Steren Chabert, Romina Torres and Rodrigo Salas
Deep learning models are part of the family of artificial neural networks and, as such, they suffer catastrophic interference when learning sequentially. In addition, the greater number of these models have a rigid architecture which prevents the increme...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ku Muhammad Naim Ku Khalif, Woo Chaw Seng, Alexander Gegov, Ahmad Syafadhli Abu Bakar and Nur Adibah Shahrul
Convolutional Neural Networks (CNNs) have garnered significant utilisation within automated image classification systems. CNNs possess the ability to leverage the spatial and temporal correlations inherent in a dataset. This study delves into the use of ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mohammad Alhumaid and Ayman G. Fayoumi
Paranasal sinus pathologies, particularly those affecting the maxillary sinuses, pose significant challenges in diagnosis and treatment due to the complex anatomical structures and diverse disease manifestations. The aim of this study is to investigate t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rokaya Eltehewy, Ahmed Abouelfarag and Sherine Nagy Saleh
Rapid damage identification and classification in disastrous situations and natural disasters are crucial for efficiently directing aid and resources. With the development of deep learning techniques and the availability of imagery content on social medi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Uddom Lee, Peng Jiang, Hongyi Wu and Chunsheng Xin
Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Karl Payne, Peter Chami, Ivanna Odle, David Oscar Yawson, Jaime Paul, Anuradha Maharaj-Jagdip and Adrian Cashman
Barbados is heavily reliant on groundwater resources for its potable water supply, with over 80% of the island?s water sourced from aquifers. The ability to meet demand will become even more challenging due to the continuing climate crisis. The consequen...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ziquan Zhu, Zeyu Ren, Siyuan Lu, Shuihua Wang and Yudong Zhang
Background: Blood is responsible for delivering nutrients to various organs, which store important health information about the human body. Therefore, the diagnosis of blood can indirectly help doctors judge a person?s physical state. Recently, researche...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jinyeong Yu, Seung Jun Oh, Seunghun Baek, Jonghyun Kim and Taekyung Lee
The multi-pass caliber rolling (MPCR) of Mg alloy has attracted much attention due to its engineering and manufacturing advantages. The MPCR process induces a unique microhardness variation, which has only been predicted using a finite element analysis t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Manuel Domínguez-Rodrigo, Ander Fernández-Jaúregui, Gabriel Cifuentes-Alcobendas and Enrique Baquedano
Deep learning models are based on a combination of neural network architectures, optimization parameters and activation functions. All of them provide exponential combinations whose computational fitness is difficult to pinpoint. The intricate resemblanc...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shuai Dong, Wei Wang, Wensheng Li and Kun Zou
A 2D floor plan (FP) often contains structural, decorative, and functional elements and annotations. Vectorization of floor plans (VFP) is an object detection task that involves the localization and recognition of different structural primitives in 2D FP...
ver más
|
|
|
|
|
|
|
|
|
|
|
Bilel Benjdira, Adel Ammar, Anis Koubaa and Kais Ouni
Despite the significant advances noted in semantic segmentation of aerial imagery, a considerable limitation is blocking its adoption in real cases. If we test a segmentation model on a new area that is not included in its initial training set, accuracy ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Angelo Casolaro, Vincenzo Capone, Gennaro Iannuzzo and Francesco Camastra
A time series is a sequence of time-ordered data, and it is generally used to describe how a phenomenon evolves over time. Time series forecasting, estimating future values of time series, allows the implementation of decision-making strategies. Deep lea...
ver más
|
|
|
|
|
|
|
|
|
|
|
Euclides Carlos Pinto Neto, Derick Moreira Baum, Jorge Rady de Almeida, Jr., João Batista Camargo, Jr. and Paulo Sergio Cugnasca
Currently, the increasing number of daily flights emphasizes the importance of air transportation. Furthermore, Air Traffic Management (ATM) enables air carriers to operate safely and efficiently through the multiple services provided. Advanced analytic ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Luigi Gianpio Di Maggio, Eugenio Brusa and Cristiana Delprete
The Intelligent Fault Diagnosis of rotating machinery calls for a substantial amount of training data, posing challenges in acquiring such data for damaged industrial machinery. This paper presents a novel approach for generating synthetic data using a G...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hafiz Suliman Munawar, Fahim Ullah, Amirhossein Heravi, Muhammad Jamaluddin Thaheem and Ahsen Maqsoom
Manual inspection of infrastructure damages such as building cracks is difficult due to the objectivity and reliability of assessment and high demands of time and costs. This can be automated using unmanned aerial vehicles (UAVs) for aerial imagery of da...
ver más
|
|
|
|
|
|
|
|
|
|
|
Anil Dogru, Soufiane Bouarfa, Ridwan Arizar and Reyhan Aydogan
Convolutional Neural Networks combined with autonomous drones are increasingly seen as enablers of partially automating the aircraft maintenance visual inspection process. Such an innovative concept can have a significant impact on aircraft operations. T...
ver más
|
|
|
|
|
|
|
|
|
|
|
Valentin Ogrean and Remus Brad
Since their inception, deep-learning architectures have shown promising results for automatic segmentation. However, despite the technical advances introduced by fully convolutional networks, generative adversarial networks or recurrent neural networks, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juan Andres Laura, Gabriel Omar Masi, Luis Argerich
Pág. 30 - 46
In recent studies Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, Data Compression is also based on prediction. What the problem come...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shayan Taheri, Aminollah Khormali, Milad Salem and Jiann-Shiun Yuan
In this work, we propose a novel defense system against adversarial examples leveraging the unique power of Generative Adversarial Networks (GANs) to generate new adversarial examples for model retraining. To do so, we develop an automated pipeline using...
ver más
|
|
|
|
|
|