Results 241 to 250 of about 729,502 (283)

High‐Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million‐Patient Diabetes Cohort

Advanced Science, EarlyView.
This study generates high‐fidelity synthetic longitudinal records for a million‐patient diabetes cohort, successfully replicating clinical predictive performance. However, deeper analysis reveals algorithmic biases and trajectory inconsistencies that escape standard quality metrics. These findings challenge current validation norms, demonstrating why a
Francisco Ortuño, Víctor M. de la Oliva Roque, Javier‐Ignacio Ramirez‐Lopez, David P. Kreil, Joaquín Dopazo, Carlos Loucera   +5 more
wiley   +1 more source

Type-2 Neutrosophic Markov Chain Model for Subject-Independent Sign Language Recognition: A New Uncertainty-Aware Soft Sensor Paradigm. [PDF]

Sensors (Basel)
Al-Saidi M, Ballagi Á, Hassen OA, Saad SM.   +3 more
europepmc   +1 more source

An Increasing Misalignment Between Crop Distribution and Environmental Resources Under Climate Change in China

Advanced Science, EarlyView.
Climate change reshapes the spatial alignment between crop production and environmental resources. Using multi‐source data and a crop model, integrated climatic, water, and soil endowments for maize and wheat are quantified and compared with harvest distributions.
Zheng'e Su, Zhentao Zhang, Jin Zhao, Xia Liang, Chuang Zhao, Zhijuan Liu, Minghao Zhuang, Jing Sun, Bo Lu, Ke Liu, Johannes W. M. Pullens, Matthew T. Harrison, Deli Chen, Xiaoguang Yang   +13 more
wiley   +1 more source

Innovative hand pose based sign language recognition using hybrid metaheuristic optimization algorithms with deep learning model for hearing impaired persons. [PDF]

Sci Rep
Alabduallah B, Al Dayil R, Al Dayil R, Alkharashi A, Alneil AA.   +4 more
europepmc   +1 more source

Sign Language Recognition System for Deaf Patients: Protocol for a Systematic Review.

JMIR Res Protoc
Marcolino MS, Oliveira LFR, Valle LR, Rosa LMMS, Reis ZSN, Soares TBC, Bernardino ELA, Cordeiro RAA, Prates RO, Campos MFM.   +9 more
europepmc   +1 more source

Retraction Note: Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network. [PDF]

Sci Rep
Pathan RK, Biswas M, Yasmin S, Khandaker MU, Salman M, Youssef AAF.   +5 more
europepmc   +1 more source

Real-Time Arabic Sign Language Recognition Using a Hybrid Deep Learning Model. [PDF]

Sensors (Basel)
Noor TH, Noor A, Alharbi AF, Faisal A, Alrashidi R, Alsaedi AS, Alharbi G, Alsanoosy T, Alsaeedi A.   +8 more
europepmc   +1 more source

LAVRF: Sign language recognition via Lightweight Attentive VGG16 with Random Forest. [PDF]

PLoS One
Ewe ELR, Lee CP, Lim KM, Kwek LC, Alqahtani A.   +4 more
europepmc   +1 more source

Sign language recognition model

Elina Singh, Aditi Balaji, K. Arthi
openaire   +1 more source

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Sign language recognition

2007 9th International Symposium on Signal Processing and Its Applications, 2007
In this paper, an image processing algorithm is presented for the interpretation of the Taiwanese sign language, which is one of the sign languages used by the majority of the deaf community. The process involves two layer classifications. At first, coarse classification is done according to detection of hand motion and tracking the hand location and ...
Maryam Pahlevanzadeh, Mansour Vafadoost, Majid Shahnazi   +2 more
openaire   +1 more source