15 papers · ranked by Valyu relevance
Seungjun Lee, Daegun Yoon, Sangho Yeo, Sangyoon Oh + 4 more
As Artificial Intelligence (AI) is becoming ubiquitous in many applications, serverless computing is also emerging as a building block for developing cloud-based AI services. Serverless computing has received much interest because of its simplicity, scalability, and resource efficiency. However, due to the trade-off…
Christopher S. Henry, Claudia Lerma-Ortiz, Svetlana Y. Gerdes, Jeffrey D. Mullen + 10 more
'Jeffrey D. Mullen' 'Ric Colasanti' 'Aleksey Zhukov' 'Océane Frelin' 'Jennifer J. Thiaville' 'Rémi Zallot' 'Thomas D. Niehaus' 'Ghulam Hasnain' 'Neal Conrad' 'Andrew D. Hanson' 'Valérie de Crécy-Lagard'] Background Gene fusions are the most powerful type of in silico-derived functional associations. However, many…
Gabriele Picco, Elisabeth D. Chen, Luz Garcia Alonso, Fiona M. Behan + 16 more
Many gene fusions are reported in tumours and for most their role remains unknown. As fusions are used for diagnostic and prognostic purposes, and are targets for treatment, it is crucial to assess their function in cancer. To systematically investigate the role of fusions in tumour cell fitness, we utilized…
Wenyu Zhang, Zhenjiang Zhang, Leonhard M. Reindl
Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective…
Ludan Chen, Shiwen Wu, Stephen C. H. Leung
Introduction The advancement of medical robotic systems highlights the critical need for precise and high-quality visual data, particularly in low-quality imaging scenarios. This study explores the interdisciplinary physics underlying image fusion and analysis, addressing challenges such as integrating complementary…
Yandong Liu, Linna Ji, Fengbao Yang, Xiaoming Guo + 1 more
Addressing the limitation of existing infrared and visible video fusion models, which fail to dynamically adjust fusion strategies based on video differences, often resulting in suboptimal or failed outcomes, we propose an infrared and visible video fusion algorithm that leverages the autonomous and flexible…
Marwah Almasri, Khaled Elleithy, Abrar Alajlan, Lianqing Liu + 4 more
Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have…
Liming Gou, Jian Zhang, Naiwen Li, Zongshui Wang + 3 more
In the process of intelligent system operation fault diagnosis and decision making, the multi-source, heterogeneous, complex, and fuzzy characteristics of information make the conflict, uncertainty, and validity problems appear in the process of information fusion, which has not been solved. In this study, we analyze…
Wenqing Wang, Ji He, Han Liu, Wei Yuan + 1 more
The fusion of multi-modal medical images has great significance for comprehensive diagnosis and treatment. However, the large differences between the various modalities of medical images make multi-modal medical image fusion a great challenge. This paper proposes a novel multi-scale fusion network based on…
Ioannis Merianos, Nikolaos Mitianoudis
Modern imaging applications have increased the demand for High-Definition Range (HDR) imaging. Nonetheless, HDR imaging is not easily available with low-cost imaging sensors, since their dynamic range is rather limited. A viable solution to HDR imaging via low-cost imaging sensors is the synthesis of multiple-exposure…
Zetian Wang, Fei Wang, Dan Wu, Guowang Gao + 3 more
'Christel-Loic Tisse'] This paper presents an algorithm for infrared and visible image fusion using significance detection and Convolutional Neural Networks with the aim of integrating discriminatory features and improving the overall quality of visual perception. Firstly, a global contrast-based significance detection…
Amita Nandal, Hamurabi Gamboa Rosales
In this paper a novel image fusion algorithm based on directional contrast in fuzzy transform (FTR) domain is proposed. Input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rule in FTR domain. The fused…
Amina Jameel, Abdul Ghafoor, Muhammad Mohsin Riaz
Improved guided image fusion for magnetic resonance and computed tomography imaging is proposed. Existing guided filtering scheme uses Gaussian filter and two-level weight maps due to which the scheme has limited performance for images having noise. Different modifications in filter (based on linear minimum mean square…
Ayush Dogra, Bhawna Goyal, Dawa Chyophel Lepcha, Ahmed Alkhayyat + 4 more
'Devendra Singh' 'Durga Prasad Bavirisetti' 'Vinay Kukreja' 'Muhammad Shahid Farid'] Multimodal medical image fusion is a perennially prominent research topic that can obtain informative medical images and aid radiologists in diagnosing and treating disease more effectively. However, the recent state-of-the-art methods…
Zhiguang Yang, Shan Zeng, Jiayi Ma, Yu Liu + 3 more
'Zheng Wang' 'Han Xu'] In this paper, we design an infrared (IR) and visible (VIS) image fusion via unsupervised dense networks, termed as TPFusion. Activity level measurements and fusion rules are indispensable parts of conventional image fusion methods. However, designing an appropriate fusion process is…