Zobrazeno 1 - 10
of 557
pro vyhledávání: '"Deep Neural Networks (DNN)"'
Publikováno v:
Leida xuebao, Vol 13, Iss 6, Pp 1298-1326 (2024)
Deep Neural Network (DNN)-based Synthetic Aperture Radar (SAR) image target recognition has become a prominent area of interest in SAR applications. However, deep neural network models are vulnerable to adversarial example attacks. Adversarial exampl
Externí odkaz:
https://doaj.org/article/0a246f6360244bf29ffc06c5160ebd60
Autor:
Anna Heinke, Haochen Zhang, Krzysztof Broniarek, Katarzyna Michalska-Małecka, Wyatt Elsner, Carlo Miguel B. Galang, Daniel N. Deussen, Alexandra Warter, Fritz Kalaw, Ines Nagel, Akshay Agnihotri, Nehal N. Mehta, Julian Elias Klaas, Valerie Schmelter, Igor Kozak, Sally L. Baxter, Dirk-Uwe Bartsch, Lingyun Cheng, Cheolhong An, Truong Nguyen, William R. Freeman
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract This study investigates the efficacy of predicting age-related macular degeneration (AMD) activity through deep neural networks (DNN) using a cross-instrument training dataset composed of Optical coherence tomography-angiography (OCTA) image
Externí odkaz:
https://doaj.org/article/f0b1c73441e648c8969d26e7c6921c1c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract The increasing interest in switchable and tunable wideband perfect absorbers for applications such as modulation, energy harvesting, and spectroscopy has significantly driven research efforts. In this study, we present a dual-function terahe
Externí odkaz:
https://doaj.org/article/6be9f440287e4f13ac5a5011f9563b26
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Under the support of deep neural networks (DNN), a multifunctional switchable terahertz metamaterial (THz MMs) device is designed and optimized. This device not only achieves ideal ultra-wideband (UWB) absorption in the THz frequency range b
Externí odkaz:
https://doaj.org/article/1f24aa54e30c4fe1b7269e434a65fb44
Publikováno v:
Smart Agricultural Technology, Vol 9, Iss , Pp 100667- (2024)
Mastitis presents a critical challenge in dairy farming, significantly impacting both animal health and economic stability. This study advances mastitis severity classification in Holstein-Friesian cows through an interdisciplinary approach that inte
Externí odkaz:
https://doaj.org/article/1ecf59b1187f4cf9a5a6feb24c00b6d5
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-33 (2024)
Abstract Autism spectrum disorder (ASD) is a complex developmental issue that affects the behavior and communication abilities of children. It is extremely needed to perceive it at an early age. The research article focuses on attentiveness by consid
Externí odkaz:
https://doaj.org/article/a9c32a5ba38c469ba96fc9439c4ea7f6
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 21, Iss 1, Pp 1-8 (2024)
Abstract Background Artificial intelligence is being used for rehabilitation, including monitoring exercise compliance through sensor technology. AI classification of shoulder exercise wearing an IMU sensor has only been reported in normal (i.e. pain
Externí odkaz:
https://doaj.org/article/e42484efd9f243089ad728e1c53aefdc
Publikováno v:
IEEE Access, Vol 12, Pp 174796-174807 (2024)
The next generation of United States Navy uncrewed aerial systems (UASs) is expected to operate in global positioning system and radio frequency-denied maritime environments. In these challenging conditions, these UASs must accurately identify specif
Externí odkaz:
https://doaj.org/article/00efe5369a434783889a3e526c90a52f
Publikováno v:
IEEE Access, Vol 12, Pp 108303-108312 (2024)
Point cloud-based deep neural networks (PC-DNNs) has seen growing interest in the construction domain due to their remarkable ability to enhance Building Information Modeling (BIM)-related tasks. Among these tasks, Industry Foundation Classes (IFC) o
Externí odkaz:
https://doaj.org/article/a406e8cebe6d4b988531c9cb4e66ec3f
Autor:
Jianwen Xu, Haitao Lang
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 5604-5620 (2024)
Improving ship classification performance in remote sensing imagery by deep metric learning (DML) is a newly emerging research topic and has good application prospects. From the perspective of the use of metric loss (classification loss and pairwise
Externí odkaz:
https://doaj.org/article/4ad0abaa39bb461a81e48b06362bee18