Zobrazeno 1 - 10
of 359
pro vyhledávání: '"group convolution"'
Publikováno v:
Virtual Reality & Intelligent Hardware, Vol 6, Iss 4, Pp 267-279 (2024)
Background: Despite the recent progress in 3D point cloud processing using deep convolutional neural networks, the inability to extract local features remains a challenging problem. In addition, existing methods consider only the spatial domain in th
Externí odkaz:
https://doaj.org/article/d43a54fe7a964e39a0ff41997635c790
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14543-14555 (2024)
Accurate medium- and long-term hydrological forecasting is crucial for sustainable water management, infrastructure planning, and ecosystem conservation. This study integrates visual geometry group convolution neural network algorithm (VGGNet)-driven
Externí odkaz:
https://doaj.org/article/ed1c72cc31534274aa692779601d350c
Publikováno v:
IEEE Access, Vol 12, Pp 67379-67391 (2024)
Accurate face recognition technology is of great significance for face anti-counterfeiting. Due to illumination, posture, angle, and other reasons, the existing face liveness detection technology is difficult to adapt the environmental changes, resul
Externí odkaz:
https://doaj.org/article/b6beb913da4b4c4ca86eac5edc8242c8
Publikováno v:
Geocarto International, Vol 38, Iss 1 (2023)
Recently, hyperspectral image (HSI) super-resolution (SR) techniques based on deep learning have been actively developed. However, most hyperspectral image super-resolution reconstruction methods usually use all spectral bands simultaneously, leading
Externí odkaz:
https://doaj.org/article/573e9f9316c7434fb101aa134a0ec2f5
Publikováno v:
Tongxin xuebao, Vol 44, Pp 124-136 (2023)
Aiming at the problem that the resources of maritime mobile terminals were limited and the network traffic was imbalanced in the MMSN (maritime meteorological sensor network) environment, which made it difficult to detect network intrusion accurately
Externí odkaz:
https://doaj.org/article/f11171ff06a14db7a4af3b8144388ab5
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 6, p 885 (2024)
Ship-radiated noise separation is critical in both military and economic domains. However, due to the complex underwater environments with multiple noise sources and reverberation, separating ship-radiated noise poses a significant challenge. Traditi
Externí odkaz:
https://doaj.org/article/51989d8a8d0d44b9b29252ad9c1ec302
Autor:
Baoxiang Chen, Xinwei Fan
Publikováno v:
Mathematics, Vol 12, Iss 10, p 1539 (2024)
Traffic sign recognition plays a crucial role in enhancing the safety and efficiency of traffic systems. However, in snowy conditions, traffic signs are often obscured by particles, leading to a severe decrease in detection accuracy. To address this
Externí odkaz:
https://doaj.org/article/b8972ddc67f34912aa7fb7777dca097e
Autor:
Tirivangani Magadza, Serestina Viriri
Publikováno v:
IEEE Access, Vol 11, Pp 126386-126397 (2023)
Brain tumors are one of the leading causes of death in adults. They come in various shapes and sizes from one patient to another. Sometimes, they infiltrate surrounding normal tissues, making it challenging to delineate tumor boundaries. Despite exte
Externí odkaz:
https://doaj.org/article/526b4c3924024836922d4626e3d0b254
Publikováno v:
IEEE Access, Vol 11, Pp 28454-28465 (2023)
In computer vision, rotation equivariance and translation invariance are properties of a representation that preserve the geometric structure of a transformed input. These properties are achieved in Convolutional Neural Networks (CNNs) through data a
Externí odkaz:
https://doaj.org/article/325d9fb67b9e46d6a47cafde55132fdf
Publikováno v:
IEEE Access, Vol 11, Pp 2361-2374 (2023)
A lightweight image recognition model, L-GhostNet based on improved GhostNet, is proposed to address the problems of extensive computation and high storage cost of deep convolutional neural networks. The model incorporated learning group convolution
Externí odkaz:
https://doaj.org/article/e06b0f4d9624474aad8a056224e305d5