Zobrazeno 1 - 10
of 25 429
pro vyhledávání: '"Deep Neural Networks"'
Autor:
Sergei Sergeev, Iuliia Diakova
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract The utilization of neural networks in assisted reproductive technology is essential due to their ability to process complex and multidimensional data inherent in IVF procedures, offering opportunities for clinical outcome prediction, persona
Externí odkaz:
https://doaj.org/article/9d0552c43d0a42af9995bb6863091430
Autor:
Aleksandr S. Pikul
Publikováno v:
Безопасность информационных технологий, Vol 31, Iss 4, Pp 116-127 (2024)
This article explores the potential use of modern computer vision architectures for the task of deepfake detection. The following architectures are considered: EfficientNet, Vision Transformer (ViT), VisionLSTM (ViL), Vision KAN, and Mamba Vision. Th
Externí odkaz:
https://doaj.org/article/34d5750983fb46b5b8523588853c0864
Publikováno v:
BMC Genomics, Vol 25, Iss 1, Pp 1-9 (2024)
Abstract Background The 5’ untranslated region of mRNA strongly impacts the rate of translation initiation. A recent convolutional neural network (CNN) model accurately quantifies the relationship between massively parallel synthetic 5’ untransla
Externí odkaz:
https://doaj.org/article/2a26e7d054e444fc8b10d4d212e31d5b
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
Autor:
Hongjiang Yang, Wenbiao Zhu, Bo Li, Hao Wang, Cong Xing, Yang Xiong, Xiuzhi Ren, Guangzhi Ning
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 19, Iss 1, Pp 1-11 (2024)
Abstract Background Osteogenesis imperfecta (OI) is a genetic disorder characterized by low bone mass, bone fragility and short stature. There is a significant gap in knowledge regarding the growth patterns across different types of OI, and the predi
Externí odkaz:
https://doaj.org/article/d2fcc0739eee4562a9c463f3187c0f75
Publikováno v:
Complex & Intelligent Systems, Vol 11, Iss 1, Pp 1-13 (2024)
Abstract Robust deep learning models have demonstrated significant applicability in real-world scenarios. The utilization of adversarial attacks plays a crucial role in assessing the robustness of these models. Among such attacks, transfer-based atta
Externí odkaz:
https://doaj.org/article/099cce3723d1447ca8dc35ff9df426bf
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 9, Iss 5, Pp 1331-1345 (2024)
Abstract Although deep convolution neural network (DCNN) has achieved great success in computer vision field, such models are considered to lack interpretability in decision‐making. One of fundamental issues is that its decision mechanism is consid
Externí odkaz:
https://doaj.org/article/ea0ff044de9147e6954baba801f74f9a
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
Autor:
Niaz Ashraf Khan, A. M. Saadman Rafat
Publikováno v:
Journal of Information and Telecommunication, Pp 1-19 (2024)
Despite all the recent development and success of deep neural networks, deployment of a deep model onto the resource-constrained devices still remains challenging. However, model pruning can resolve this issue for Convolutional Neural Networks (CNNs)
Externí odkaz:
https://doaj.org/article/75d70d0a7d4e4e1cb34ea813312b971b
Publikováno v:
EURASIP Journal on Information Security, Vol 2024, Iss 1, Pp 1-26 (2024)
Abstract Deep neural networks (DNNs) are fundamental to modern applications like face recognition and autonomous driving. However, their security is a significant concern due to various integrity risks, such as backdoor attacks. In these attacks, com
Externí odkaz:
https://doaj.org/article/229e33be82d445109cd7a79e10e521f3