Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Maoshen Jia"'
Publikováno v:
IET Image Processing, Vol 18, Iss 13, Pp 4411-4421 (2024)
Abstract Timely detection of hard exudates in fundus images can effectively avoid the severity of the disease, but the labelling of small and numerous lesion areas requires a lot of labour costs. This paper proposes a semi‐supervised segmentation n
Externí odkaz:
https://doaj.org/article/293d5867e8e44777b50566a57adcbdab
Publikováno v:
IET Image Processing, Vol 18, Iss 7, Pp 1878-1891 (2024)
Abstract Combining the extracted tongue features with other medical indicators can effectively judge the diseases of patients. The previous work usually only analyzes a certain feature of the tongue body and is unable to extract multiple features sim
Externí odkaz:
https://doaj.org/article/6ec05145a3c14a6c9aab5354394b6749
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-18 (2024)
Abstract Dynamic parameterization of acoustic environments has drawn widespread attention in the field of audio processing. Precise representation of local room acoustic characteristics is crucial when designing audio filters for various audio render
Externí odkaz:
https://doaj.org/article/9fcc8b0da1ea4c309c57ce37a93aca54
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2023, Iss 1, Pp 1-16 (2023)
Abstract In recent years, the speaker-independent, single-channel speech separation problem has made significant progress with the development of deep neural networks (DNNs). However, separating the speech of each interested speaker from an environme
Externí odkaz:
https://doaj.org/article/bcd9416ae3394a339d52ce956b644972
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 8, Iss 3, Pp 807-823 (2023)
Abstract Multisource localization occupies an important position in the field of acoustic signal processing and is widely applied in scenarios, such as human‐machine interaction and spatial acoustic parameter acquisition. The direction‐of‐arriv
Externí odkaz:
https://doaj.org/article/503f9f16fbdd44b1a027cdf624962fc4
Publikováno v:
IET Image Processing, Vol 17, Iss 11, Pp 3337-3348 (2023)
Abstract Accurate segmentation of hard exudates in early non‐proliferative diabetic retinopathy can assist physicians in taking appropriate treatment in a more targeted manner, in order to avoid more serious damage to vision caused by the deteriora
Externí odkaz:
https://doaj.org/article/1d31497c63c94d84b2a64b110c5b562d
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2022, Iss 1, Pp 1-20 (2022)
Abstract Speech emotion recognition (SER) is a hot topic in speech signal processing. When the training data and the test data come from different corpus, their feature distributions are different, which leads to the degradation of the recognition pe
Externí odkaz:
https://doaj.org/article/b68453e7c64b4d159f1c2f38386f9d7d
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2021, Iss 1, Pp 1-18 (2021)
Abstract Multiple sound source localization is a hot issue of concern in recent years. The Single Source Zone (SSZ) based localization methods achieve good performance due to the detection and utilization of the Time-Frequency (T-F) zone where only o
Externí odkaz:
https://doaj.org/article/a3be92935d774223810b06c47c6c5ee9
Publikováno v:
Applied Sciences, Vol 12, Iss 12, p 6224 (2022)
Multiple sound source separation in a reverberant environment has become popular in recent years. To improve the quality of the separated signal in a reverberant environment, a separation method based on a DOA cue and a deep neural network (DNN) is p
Externí odkaz:
https://doaj.org/article/46faa781036b41dfb3287ba7902f92ba
Publikováno v:
IEEE Access, Vol 6, Pp 54550-54563 (2018)
This paper proposes a 3-D sound field reproduction (SFR) approach through the combination of alternating direction method of multipliers (ADMM)-based least-absolute shrinkage and selection operator (Lasso) and regularized least square (LS). The propo
Externí odkaz:
https://doaj.org/article/b8979828ed2648c4b76f07ecd64cd250