Zobrazeno 1 - 10
of 246
pro vyhledávání: '"Neural net architecture"'
Publikováno v:
IET Computer Vision, Vol 18, Iss 7, Pp 992-1003 (2024)
Abstract Human action recognition based on graph convolutional networks (GCNs) is one of the hotspots in computer vision. However, previous methods generally rely on handcrafted graph, which limits the effectiveness of the model in characterising the
Externí odkaz:
https://doaj.org/article/617303b98b5448678cac64dc5045540e
Publikováno v:
IET Renewable Power Generation, Vol 18, Iss 14, Pp 2195-2208 (2024)
Abstract Accurate estimation of wind power is essential for predicting and maintaining the power balance in the power system. This paper proposes a novel approach to enhance the accuracy of wind power estimation through a hybrid model integrating neu
Externí odkaz:
https://doaj.org/article/e997f67410534aacb1a77c5c2b983eb7
Autor:
Dongting Zhang, Hongbin Ma
Publikováno v:
IET Image Processing, Vol 18, Iss 12, Pp 3699-3715 (2024)
Abstract Most multiple object tracking algorithms depend on the output of the detector. Aiming at the problem that the higher detection quality model is restricted by the computing power, and the robustness of the lightweight detection model is easil
Externí odkaz:
https://doaj.org/article/5f5b81e511024985b54e400940a8465e
Publikováno v:
IET Image Processing, Vol 18, Iss 12, Pp 3480-3495 (2024)
Abstract Intracranial hematoma, a severe brain injury caused by trauma or cerebrovascular disease, can result in blood accumulation and compression of brain tissue. Untreated cases can cause headaches, impaired consciousness, and even brain tissue da
Externí odkaz:
https://doaj.org/article/7fb889a4509d4c17812fa45ff869d067
Publikováno v:
Cognitive Computation and Systems, Vol 6, Iss 1-3, Pp 1-11 (2024)
Abstract The ability to effectively classify human emotion states is critically important for human‐computer or human‐robot interactions. However, emotion classification with physiological signals is still a challenging problem due to the diversi
Externí odkaz:
https://doaj.org/article/528d715e4a3d445eb64efcbfd0295842
Publikováno v:
IET Image Processing, Vol 18, Iss 11, Pp 2899-2917 (2024)
Abstract Head pose estimation is an especially challenging task due to the complexity nonlinear mapping from 2D feature space to 3D pose space. To address the above issue, this paper presents a novel and efficient head pose estimation framework based
Externí odkaz:
https://doaj.org/article/53931f7ebc4347659249b4e800789c63
Publikováno v:
IET Computer Vision, Vol 18, Iss 5, Pp 574-590 (2024)
Abstract In response to the challenges of Multi‐Object Tracking (MOT) in sports scenes, such as severe occlusions, similar appearances, drastic pose changes, and complex motion patterns, a deep‐learning framework CTGMOT (CNN‐Transformer‐GNN
Externí odkaz:
https://doaj.org/article/0b318480927d46249d511b96b4708a12
Publikováno v:
IET Computer Vision, Vol 18, Iss 5, Pp 640-651 (2024)
Abstract The multifaceted nature of sensor data has long been a hurdle for those seeking to harness its full potential in the field of 3D object detection. Although the utilisation of point clouds as input has yielded exceptional results, the challen
Externí odkaz:
https://doaj.org/article/ea606cd8d2ee42698ec76818b6fc1d9e
Autor:
Md. Shakib Shahariar Junayed, Kazi Shahriar Sanjid, Md. Tanzim Hossain, M. Monir Uddin, Sheikh Anisul Haque
Publikováno v:
IET Image Processing, Vol 18, Iss 10, Pp 2745-2753 (2024)
Abstract This research investigates the Circle of Willis, a critical vascular structure vital for cerebral blood supply. A modified novel dual‐pathway multi‐scale hierarchical upsampling network (HUNet) is presented, tailored explicitly for accur
Externí odkaz:
https://doaj.org/article/9fa3852f1e734db78cb736064afe68f1
Publikováno v:
Electronics Letters, Vol 60, Iss 20, Pp n/a-n/a (2024)
Abstract Multivariate time series forecasting is widely used in various fields in real life. Many time series prediction models have been proposed. The current forecasting model lacks the mining of correlation between sequences based on different per
Externí odkaz:
https://doaj.org/article/b726912edbcf43fbacc677d5544f38f3