Zobrazeno 1 - 10
of 3 467
pro vyhledávání: '"Learning (artificial intelligence)"'
Publikováno v:
IET Communications, Vol 18, Iss 16, Pp 966-977 (2024)
Abstract Kidney tumours are among the top ten most common tumours, the automatic segmentation of medical images can help locate tumour locations. However, the segmentation of kidney tumour images still faces several challenges: firstly, there is a la
Externí odkaz:
https://doaj.org/article/8e9a63efa1254197837f3a65abcf7af2
Publikováno v:
IET Generation, Transmission & Distribution, Vol 18, Iss 19, Pp 3071-3084 (2024)
Abstract As an emerging multi‐energy consumption subject, data centres (DCs) are bound to become crucial energy users for integrated energy systems (IES). Therefore, how to fully tap the potential of the collaborative operation between DCs and IES
Externí odkaz:
https://doaj.org/article/23dda53cb1b945a09e963786ec759fe8
Autor:
Maha Al‐Sharif, Anas Bushnag
Publikováno v:
IET Communications, Vol 18, Iss 16, Pp 950-965 (2024)
Abstract Cloud computing has become an essential technology for people and enterprises due to the simplicity and rapid availability of services on the internet. These services are usually delivered through a third party, which provides the required r
Externí odkaz:
https://doaj.org/article/ea9ffb8b4c4d4c63a1505cc54b8e4e70
Publikováno v:
IET Generation, Transmission & Distribution, Vol 18, Iss 19, Pp 3138-3149 (2024)
Abstract Bird‐related outages greatly threaten the safety of overhead transmission and distribution lines, while electrocution and collisions of birds with power lines, especially endangered species, are significant environmental concerns. Automati
Externí odkaz:
https://doaj.org/article/9ec9da323c4b4564b4ad4e18b2eee58d
Publikováno v:
IET Generation, Transmission & Distribution, Vol 18, Iss 18, Pp 2943-2955 (2024)
Abstract Thanks to reinforcement learning (RL), decision‐making is more convenient and more economical in different situations with high uncertainty. In line with the same fact, it is proposed that prosumers can apply RL to earn more profit in the
Externí odkaz:
https://doaj.org/article/38638c84a6444ef3b8f0ed924b20bfbb
Publikováno v:
IET Image Processing, Vol 18, Iss 11, Pp 2962-2973 (2024)
Abstract Recent advancements in deep learning have significantly improved performance in the multi‐view stereo (MVS) domain, yet achieving a balance between reconstruction efficiency and quality remains challenging for learning‐based MVS methods.
Externí odkaz:
https://doaj.org/article/af099f21d76f461a970c93171e3fa108
Publikováno v:
IET Control Theory & Applications, Vol 18, Iss 13, Pp 1649-1668 (2024)
Abstract Trained deep reinforcement learning (DRL) based controllers can effectively control dynamic systems where classical controllers can be ineffective and difficult to tune. However, the lack of closed‐loop stability guarantees of systems cont
Externí odkaz:
https://doaj.org/article/a723b06f96124e27bb70bc0380023ee0
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 9, Iss 4, Pp 973-981 (2024)
Abstract Offline reinforcement learning (RL) aims to learn policies entirely from passively collected datasets, making it a data‐driven decision method. One of the main challenges in offline RL is the distribution shift problem, which causes the al
Externí odkaz:
https://doaj.org/article/5d4176ad6c344b938513a986a45e3eea
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 9, Iss 4, Pp 903-916 (2024)
Abstract A comparative study of two force perception skill learning approaches for robot‐assisted spinal surgery, the impedance model method and the imitation learning (IL) method, is presented. The impedance model method develops separate models f
Externí odkaz:
https://doaj.org/article/f51d81bc356e4215a929019a2ddb2bdb
Publikováno v:
IET Image Processing, Vol 18, Iss 10, Pp 2553-2567 (2024)
Abstract Due to differences in the quantity and size of observed targets, hyperspectral images are characterized by class imbalance. The standard deep learning classification model training scheme optimizes the overall classification error, which may
Externí odkaz:
https://doaj.org/article/10539116ff0b4f1ea71a54476a63e792