Zobrazeno 1 - 10
of 874
pro vyhledávání: '"neighbor embedding"'
Publikováno v:
Научный вестник МГТУ ГА, Vol 27, Iss 2, Pp 8-24 (2024)
The paper considers the application of pretrained neural networks to solve the problem of reverse searching of X-ray images of prohibited items and substances. The purpose of the work is to conduct an analysis and substantiate ways to improve the eff
Externí odkaz:
https://doaj.org/article/d7555bcec915459988a76631ce2b1a12
Autor:
Sheikh Muhammad Saqib, Tehseen Mazhar, Muhammad Iqbal, Tariq Shahazad, Ahmad Almogren, Khmaies Ouahada, Habib Hamam
Publikováno v:
Heliyon, Vol 10, Iss 15, Pp e35167- (2024)
In developing countries, smart grids are nonexistent, and electricity theft significantly hampers power supply. This research introduces a lightweight deep-learning model using monthly customer readings as input data. By employing careful direct and
Externí odkaz:
https://doaj.org/article/8db7021669b842e18fc69bb930c07976
Publikováno v:
IEEE Access, Vol 12, Pp 90380-90394 (2024)
Stochastic neighbor embedding (SNE) performs nonlinear transformation from high-dimensional observation space to low-dimensional latent space which preserves neighbor affinities. Data pairs in latent space tend to be crowded due to the dimensionality
Externí odkaz:
https://doaj.org/article/9ab8f2f9a23743cfb65272a4e31d3c8f
Autor:
Fengshun Jiao, Zhikeng Li, Jingwen Ai, Haisen Yang, Yongsheng Deng, Duo Li, Weijie Gao, Zhaoyang Lai, Xieli Fu
Publikováno v:
IEEE Access, Vol 12, Pp 83600-83610 (2024)
Correctly identifying the topology of a low-voltage distribution network aids in its management by power companies. However, the low collection rate and poor quality of the customer data collected by smart meters create difficulties in the applicatio
Externí odkaz:
https://doaj.org/article/dc23a2ea6adf46b2b58a9f714eb0bdf5
Autor:
Joydeep Ghosh
Publikováno v:
Machine Learning with Applications, Vol 16, Iss , Pp 100537- (2024)
Integral to the success of transistor advancements is the accurate use of failure analysis (FA) which benefits in fine-tuning and optimization of the fabrication processes. However, the chip makers face several FA challenges as device sizes, structur
Externí odkaz:
https://doaj.org/article/8e2ef7af23294243ab2561daaa74d604
Autor:
Chao Li, Maozhi Xiao, Suxia Geng, Yulian Wang, Lingji Zeng, Peilong Lai, Ying Gong, Xiaomei Chen
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
IntroductionExploring monocytes’ roles within the tumor microenvironment is crucial for crafting targeted cancer treatments.MethodsThis study unveils a novel methodology utilizing four 20-color flow cytometry panels for comprehensive peripheral imm
Externí odkaz:
https://doaj.org/article/619d03afec874c2da889396cae455022
Autor:
Chao Fang, Shanbang Zhu, Rui Zhong, Gang Yu, Shuai Lu, Zhilin Liu, Jingyu Gao, Chengyuan Yan, Yingming Wang, Xinzhe Feng
Publikováno v:
Heliyon, Vol 10, Iss 5, Pp e27466- (2024)
Objective: Chondrocyte death is the hallmark of cartilage degeneration during osteoarthritis (OA). However, the specific pathogenesis of cell death in OA chondrocytes has not been elucidated. This study aims to validate the role of CDKN1A, a key prog
Externí odkaz:
https://doaj.org/article/c6fe471a0dd4459d9d1c64f24c97cf44
Publikováno v:
Mathematics, Vol 12, Iss 12, p 1885 (2024)
Magnetic resonance imaging and computed tomography produce three-dimensional volumetric medical images. While a scalar value represents each individual volume element, or voxel, volumetric data are characterized by features derived from groups of nei
Externí odkaz:
https://doaj.org/article/deda9249bf784d47b917cee6869b7171
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 16, Iss 1, Pp 1-14 (2023)
Abstract The purpose of feature learning is to obtain effective representation of the raw data and then improve the performance of machine learning algorithms such as clustering or classification. Some of the existing feature learning algorithms use
Externí odkaz:
https://doaj.org/article/dd099d18b70744e98066c815aa869269
Publikováno v:
Gong-kuang zidonghua, Vol 49, Iss 1, Pp 116-122 (2023)
With the acceleration of intelligent construction of coal mines, efficient recognition of coal and rock has become a technical problem to be solved urgently in intelligent coal mining. The existing coal and rock recognition methods under complex coal
Externí odkaz:
https://doaj.org/article/5cd759c33d994ba38fdf19af64bb43b1