Zobrazeno 1 - 10
of 9 026
pro vyhledávání: '"Activation function"'
Autor:
Chibuzo Cosmas Nwanwe, Ugochukwu Ilozurike Duru, Charley Iyke C. Anyadiegwu, Azunna I. B. Ekejuba, Stanley I. Onwukwe, Angela N. Nwachukwu, Boniface U. Okonkwo
Publikováno v:
Journal of Engineering and Applied Science, Vol 71, Iss 1, Pp 1-35 (2024)
Abstract Slug liquid holdup (SLH) is a critical requirement for accurate pressure drop prediction during multiphase pipe flows and by extension optimal gas lift design and production optimization in wellbores. Existing empirical correlations provide
Externí odkaz:
https://doaj.org/article/9842c397fa7c445d9f27e1aefd0ea24f
Autor:
Akhrorjon Akhmadjon Ugli Rakhmonov, Barathi Subramanian, Bahar Amirian Varnousefaderani, Jeonghong Kim
Publikováno v:
ETRI Journal, Vol 46, Iss 5, Pp 890-903 (2024)
Anomaly detection in video surveillance is crucial but challenging due to the rarity of irregular events and ambiguity of defining anomalies. We propose a method called AONet that utilizes a spatiotemporal module to extract spatio-temporal features e
Externí odkaz:
https://doaj.org/article/6390743dfe4046f2a095884d7cbb8be8
Autor:
Chandrasekaran Raja, Santhosh Krishna B V, Balaji Loganathan, Sanjay Kumar Suman, L. Bhagyalakshmi, Mubarak Alrashoud, Jayant Giri, T. Sathish
Publikováno v:
Automatika, Vol 65, Iss 4, Pp 1593-1605 (2024)
This work modifies the architecture of conventional CNN with the integration of Multi-resolution Analysis (MRA) in a CNN framework for Diabetic Retinopathy (DR) diagnosis and grading. Here, the HF sub-bands are subjected to optimized activations and
Externí odkaz:
https://doaj.org/article/f6c7f939f119483ba7a026ce51e7be70
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-27 (2024)
Abstract Physics informed neural network (PINN) demonstrates powerful capabilities in solving forward and inverse problems of nonlinear partial differential equations (NLPDEs) through combining data-driven and physical constraints. In this paper, two
Externí odkaz:
https://doaj.org/article/416c5f970fde45829a6ca2accf6559a8
Autor:
Hari M. Srivastava, Nazar Khan, Muhtarr A. Bah, Ayman Alahmade, Ferdous M. O. Tawfiq, Zainab Syed
Publikováno v:
Journal of Inequalities and Applications, Vol 2024, Iss 1, Pp 1-18 (2024)
Abstract The aim of this paper is to introduce two new subclasses R sin m ( ℑ ) $\mathcal{R}_{\sin }^{m}(\Im )$ and R sin ( ℑ ) $\mathcal{R}_{\sin }(\Im )$ of analytic functions by making use of subordination involving the sine function and the m
Externí odkaz:
https://doaj.org/article/685c0870c7de46efa12611b9720ee3d8
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
Negligence of public transport drivers due to drowsiness poses risks not only to their own lives but also to the lives of passengers. The designed journey tracker system alerts the drivers and activates potential penalties. A custom EfficientNet mode
Externí odkaz:
https://doaj.org/article/b528efceccf74ef1ac517f2083dd430e
Autor:
Meinard Müller, Ching-Yu Chiu
Publikováno v:
Transactions of the International Society for Music Information Retrieval, Vol 7, Iss 1, Pp 179–194-179–194 (2024)
In Music Information Retrieval (MIR), a general goal is to recognize times of novelty within music recordings. This includes estimating structural boundaries through the detection of changes in harmony, tempo, or instrumentation and identifying onset
Externí odkaz:
https://doaj.org/article/7e329f99672a4a9ab690f7f0aa8ef393
Publikováno v:
Electronic Research Archive, Vol 32, Iss 4, Pp 2699-2727 (2024)
In this paper, an accurate fractional physical information neural network with an adaptive learning rate (adaptive-fPINN-PQI) was first proposed for solving fractional partial differential equations. First, piecewise quadratic interpolation (PQI) in
Externí odkaz:
https://doaj.org/article/2321f07888b14bd1a11fd476672bfb30
Autor:
Khang Wen Goh, Sugiyarto Surono, M. Y. Firza Afiatin, K. Robiatul Mahmudah, Nursyiva Irsalinda, Mesith Chaimanee, Choo Wou Onn
Publikováno v:
Emerging Science Journal, Vol 8, Iss 2, Pp 592-602 (2024)
Deep learning, specifically the Convolutional Neural Network (CNN), has been a significant technology tool for image processing and human health. CNNs, which mimic the working principles of the human brain, can learn robust representations of images.
Externí odkaz:
https://doaj.org/article/15705a347de4442a8e2cd81356f15e89
Publikováno v:
Journal of Natural Fibers, Vol 21, Iss 1 (2024)
The current advanced neural network models are expanding in size and complexity to achieve improved detection accuracy. This study designs a lightweight fabric defect detection algorithm based on YOLOv7-tiny, called YOLOv7-tiny-MGCK. Its objectives a
Externí odkaz:
https://doaj.org/article/a4cd021ce1274015bb3affcbe29ef138