Zobrazeno 1 - 10
of 301
pro vyhledávání: '"single-object tracking"'
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-16 (2024)
Abstract With the continuous development of science and technology, intelligent surveillance technology using image processing and computer vision is also progressing. To improve the performance of target detection and tracking, an improved target tr
Externí odkaz:
https://doaj.org/article/e09e9d803c694bba9d96fff99f5ae600
Publikováno v:
IEEE Access, Vol 12, Pp 130896-130913 (2024)
In view of the complexity, uncertainty, and low visibility of the night-time environment. In this study, we designed an unsupervised domain adaptation framework, TransffCAR, using a Siamese network of the source (daytime) and target (nighttime) domai
Externí odkaz:
https://doaj.org/article/81d3674704f8484c9b5ef57b6da4f030
Publikováno v:
Applied Sciences, Vol 14, Iss 18, p 8199 (2024)
Single-object tracking algorithms based on Siamese full convolutional networks have attracted much attention from researchers owing to their improvement in precision and speed. Since this tracking model only learns a similarity model offline, it is n
Externí odkaz:
https://doaj.org/article/37498926496549d381a715b9477794c1
Publikováno v:
Remote Sensing, Vol 16, Iss 13, p 2322 (2024)
Three-dimensional (3D) single-object tracking (3D SOT) is a fundamental yet not well-solved problem in 3D vision, where the complexity of feature matching and the sparsity of point clouds pose significant challenges. To handle abrupt changes in appea
Externí odkaz:
https://doaj.org/article/282a3ae3a1e8442fa21b777fb0c5436e
Publikováno v:
GIScience & Remote Sensing, Vol 60, Iss 1 (2023)
High-resolution satellite videos realize the short-dated gaze observation of the designated area on the ground, and its emergence has improved the temporal resolution of remote sensing data to the second level. Single object tracking (SOT) task in sa
Externí odkaz:
https://doaj.org/article/9b3efe3b09ff469bbc8a3f5f05864abf
Publikováno v:
IEEE Access, Vol 11, Pp 139211-139222 (2023)
Deep neural network-based tracking tasks have experienced significant advancements in recent years. However, these networks continue to face challenges in effectively adapting to appearance changes in both target and background, as well as linking ob
Externí odkaz:
https://doaj.org/article/2e65ac09f4094c5b8f380b969a66913f
Autor:
Chao Zhang
Publikováno v:
IEEE Access, Vol 11, Pp 74855-74864 (2023)
Current mainstream single-object trackers adopt the Transformer as the backbone for target tracking. However, due to the Transformer’s limitations in local information acquisition and position encoding, we proposed a new tracking framework called C
Externí odkaz:
https://doaj.org/article/03d959c77adc4ebb8e48e8b31b6d61e6
Autor:
Junyu Fan, Shunping Ji
Publikováno v:
Remote Sensing, Vol 16, Iss 8, p 1347 (2024)
Object tracking in satellite videos has garnered significant attention due to its increasing importance. However, several challenging attributes, such as the presence of tiny objects, occlusions, similar objects, and background clutter interference,
Externí odkaz:
https://doaj.org/article/e05d640ba45c4f91931edcd873ba6248
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