345   Artículos

 
en línea
Shui Jiang, Yanning Ge, Xu Yang, Wencheng Yang and Hui Cui    
Reinforcement learning (RL) is pivotal in empowering Unmanned Aerial Vehicles (UAVs) to navigate and make decisions efficiently and intelligently within complex and dynamic surroundings. Despite its significance, RL is hampered by inherent limitations su... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Fabi Prezja, Leevi Annala, Sampsa Kiiskinen and Timo Ojala    
Diagnosing knee joint osteoarthritis (KOA), a major cause of disability worldwide, is challenging due to subtle radiographic indicators and the varied progression of the disease. Using deep learning for KOA diagnosis requires broad, comprehensive dataset... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Junlin Lou, Burak Yuksek, Gokhan Inalhan and Antonios Tsourdos    
In this study, we consider the problem of motion planning for urban air mobility applications to generate a minimal snap trajectory and trajectory that cost minimal time to reach a goal location in the presence of dynamic geo-fences and uncertainties in ... ver más
Revista: Aerospace    Formato: Electrónico

 
en línea
Navid Khalili Dizaji and Mustafa Dogan    
Brain tumors are one of the deadliest types of cancer. Rapid and accurate identification of brain tumors, followed by appropriate surgical intervention or chemotherapy, increases the probability of survival. Accurate determination of brain tumors in MRI ... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Zhichao Chen, Guoqiang Wang, Tao Lv and Xu Zhang    
Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emergenc... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim    
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Woonghee Lee and Younghoon Kim    
This study introduces a deep-learning-based framework for detecting adversarial attacks in CT image segmentation within medical imaging. The proposed methodology includes analyzing features from various layers, particularly focusing on the first layer, a... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Hassan Khazane, Mohammed Ridouani, Fatima Salahdine and Naima Kaabouch    
With the rapid advancements and notable achievements across various application domains, Machine Learning (ML) has become a vital element within the Internet of Things (IoT) ecosystem. Among these use cases is IoT security, where numerous systems are dep... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Dongming Wang, Li Xu, Wei Gao, Hongwei Xia, Ning Guo and Xiaohan Ren    
As an extremely important energy source, improving the efficiency and accuracy of coal classification is important for industrial production and pollution reduction. Laser-induced breakdown spectroscopy (LIBS) is a new technology for coal classification ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Pedro Celard, Adrián Seara Vieira, José Manuel Sorribes-Fdez, Eva Lorenzo Iglesias and Lourdes Borrajo    
In this study, we propose a novel Temporal Development Generative Adversarial Network (TD-GAN) for the generation and analysis of videos, with a particular focus on biological and medical applications. Inspired by Progressive Growing GAN (PG-GAN) and Tem... ver más
Revista: Information    Formato: Electrónico

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