Zobrazeno 1 - 10
of 12 036
pro vyhledávání: '"sliding window"'
Autor:
Sreedevi R. Krishnan, P. Amudha
Publikováno v:
Информатика и автоматизация, Vol 23, Iss 6, Pp 1899-1930 (2024)
Computer vision video anomaly detection still needs to be improved, especially when identifying images with unusual motions or objects. Current approaches mainly concentrate on reconstruction and prediction methods, and unsupervised video anomaly det
Externí odkaz:
https://doaj.org/article/debc1e6516b04609a7e30d6bad02066b
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract In this paper, we present a machine learning-based approach that leverages Long Short-Term Memory (LSTM) networks combined with a sliding window technique for feature extraction, aimed at accurately predicting point defect percentages in sem
Externí odkaz:
https://doaj.org/article/9bbe2b59f56b4bf4b743b353ee361352
Publikováno v:
Geo-spatial Information Science, Pp 1-13 (2024)
In the processing of Precise Point Positioning (PPP) data, the receiver clock is approached with nearly infinite uncertainty, rendering it difficult to fulfill the requirements of high-precision time frequency applications. Therefore, a receiver cloc
Externí odkaz:
https://doaj.org/article/034876a6ff7c41d5a9351dc286c106d8
Publikováno v:
ETRI Journal, Vol 46, Iss 4, Pp 604-618 (2024)
In wireless sensor network (WSN) monitoring systems, redundant data from sluggish environmental changes and overlapping sensing ranges can increase the volume of data sent by nodes, degrade the efficiency of information collection, and lead to the de
Externí odkaz:
https://doaj.org/article/b5500ffc7ae746f38025113cf0e6d0dc
Publikováno v:
Tongxin xuebao, Vol 45, Pp 171-183 (2024)
In the medical field, the recognition of medical entities is often influenced by their adjacent context, the current named entity recognition methods typically rely on BiLSTM to capture the global dependency relationships within text, lacking modelin
Externí odkaz:
https://doaj.org/article/94cff15525384f539632f2e6ff4ed162
Publikováno v:
Kongzhi Yu Xinxi Jishu, Iss 3, Pp 115-121 (2024)
The rapid detection of grid voltage faults is crucial to achieve grid voltage fault ride-through. However, conventional grid voltage detection methods, including Fourier transform, dq axis transform, wavelet transform, and voltage peak methods, gener
Externí odkaz:
https://doaj.org/article/c9293706298c44d6baf1bd417e4f9408
Autor:
Tyas Setiyorini, Frieyadie
Publikováno v:
Jurnal Riset Informatika, Vol 6, Iss 3, Pp 159-166 (2024)
The increase in confirmed cases and deaths due to Covid-10 continues to spread and increase day by day throughout the world. This has resulted in a world health crisis that impacts all sectors of life. The government declared a movement to suppress t
Externí odkaz:
https://doaj.org/article/84acb2c14dbd4a5bb994f9bd21bd332d
Publikováno v:
ICT Express, Vol 10, Iss 3, Pp 513-518 (2024)
In this paper, a bi-directional sliding window decoder is proposed for spatially coupled low-density parity-check (SC-LDPC) codes, which improves the decoding complexity and performance compared to the conventional sliding window decoding (SWD) by sh
Externí odkaz:
https://doaj.org/article/95aa3bbddf6145e0a67841db8af1b807
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 58, Iss , Pp 101845- (2024)
The development of fast and cost-effective methods for measuring biological molecules has many advantages over conventional methods. However, these methods, which are used for monitoring biological molecules, have some drawbacks, such as high cost, t
Externí odkaz:
https://doaj.org/article/ad5a90ce84d74c51b91e6475be2ed8f5
Publikováno v:
Green Energy and Intelligent Transportation, Vol 3, Iss 5, Pp 100178- (2024)
Railroad condition monitoring is paramount due to frequent passage through densely populated regions. This significance arises from the potential consequences of accidents such as train derailments, hazardous materials leaks, or collisions which may
Externí odkaz:
https://doaj.org/article/ba39701bba054a5caa2d0b4c6a647250