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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...
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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...
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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 ...
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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 ...
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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...
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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...
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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...
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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...
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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 ...
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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...
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