|
|
|
|
|
Ancilon Leuch Alencar, Marcelo Dornbusch Lopes, Anita Maria da Rocha Fernandes, Julio Cesar Santos dos Anjos, Juan Francisco De Paz Santana and Valderi Reis Quietinho Leithardt
In the current era of social media, the proliferation of images sourced from unreliable origins underscores the pressing need for robust methods to detect forged content, particularly amidst the rapid evolution of image manipulation technologies. Existin...
ver más
|
|
|
|
|
|
|
|
|
|
|
JongBae Kim
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jin-Woo Kong, Byoung-Doo Oh, Chulho Kim and Yu-Seop Kim
Intracerebral hemorrhage (ICH) is a severe cerebrovascular disorder that poses a life-threatening risk, necessitating swift diagnosis and treatment. While CT scans are the most effective diagnostic tool for detecting cerebral hemorrhage, their interpreta...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nils Hütten, Miguel Alves Gomes, Florian Hölken, Karlo Andricevic, Richard Meyes and Tobias Meisen
Quality assessment in industrial applications is often carried out through visual inspection, usually performed or supported by human domain experts. However, the manual visual inspection of processes and products is error-prone and expensive. It is ther...
ver más
|
|
|
|
|
|
|
|
|
|
|
Diya Wang, Yonglin Zhang, Lixin Wu, Yupeng Tai, Haibin Wang, Jun Wang, Fabrice Meriaudeau and Fan Yang
In recent years, the study of deep learning techniques for underwater acoustic channel estimation has gained widespread attention. However, existing neural network channel estimation methods often overfit to training dataset noise levels, leading to dimi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
ver más
|
|
|
|
|
|
|
|
|
|
|
Oscar Leonardo García-Navarrete, Oscar Santamaria, Pablo Martín-Ramos, Miguel Ángel Valenzuela-Mahecha and Luis Manuel Navas-Gracia
Corn (Zea mays L.) is one of the most important cereals worldwide. To maintain crop productivity, it is important to eliminate weeds that compete for nutrients and other resources. The eradication of these causes environmental problems through the use of...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ying Chen, Xi Qiao, Feng Qin, Hongtao Huang, Bo Liu, Zaiyuan Li, Conghui Liu, Quan Wang, Fanghao Wan, Wanqiang Qian and Yiqi Huang
Invasive plant species pose significant biodiversity and ecosystem threats. Real-time identification of invasive plants is a crucial prerequisite for early and timely prevention. While deep learning has shown promising results in plant recognition, the u...
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
|
|
|
|
|
|
|
|
|
|
|
Thomas Kopalidis, Vassilios Solachidis, Nicholas Vretos and Petros Daras
Recent technological developments have enabled computers to identify and categorize facial expressions to determine a person?s emotional state in an image or a video. This process, called ?Facial Expression Recognition (FER)?, has become one of the most ...
ver más
|
|
|
|
|
|