Results 111 to 120 of about 632,855 (302)

ADLAB: Aspetti di un progetto sull’audiodescrizione [PDF]

, 2014
Il contributo \ue8 interamente dedicato al progetto europeo ADLAB (Audio Description: Lifelong Learning for the Blind) del quale si espongono finalit\ue0 e natura.
Taylor, Christopher
core   +1 more source

IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition

Advanced Intelligent Systems, EarlyView.
This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi, Olatunji Omisore, Wenjing Du, Wenke Duan, Chen Bailang, Liu Kun, Lei Wang, Minxin Wei   +7 more
wiley   +1 more source

Audio Description as a Learning Aid for Students with Cognitive Disabilities: A Reception Study

Anglica. An International Journal of English Studies
In this paper, we present the results of a reception study carried out in Catalonia to explore how audio description can help cognitively diverse individuals understand films.
Yolanda Moreno Montaño, Floriane Bardini   +1 more
doaj   +1 more source

Automatic noise limiter-blanker [PDF]

A blanker system that may be used with audio noise limiters or automatic noise limiters was described. The system employs a pair of silicon diodes and two RC filters connected across the feedback impedance of an operational amplifier so as to counteract ...
Burhans, R. W.
core   +1 more source

Tracking multimodal cohesion in Audio Description: Examples from a Dutch audio description corpus

Linguistica Antverpiensia, New Series – Themes in Translation Studies, 2019
One of the main questions addressed by multimodality research—the main conceptual framework for analysing audiovisual texts—is how the different modes of audiovisual texts combined—visual, verbal, aural—create supplementary meaning in texts, over and above the meanings conveyed by the individual constituents.
openaire   +3 more sources

Autonomous Recognition of Retained Secretions in Central‐Airway Based on Deep Learning for Adult Patients Receiving Invasive Mechanical Ventilation

Advanced Intelligent Systems, EarlyView.
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang, Zhuoran Xiao, Meng Wang, Jianchao Li, Chunjing Tao, Jiangzhen Guo, Yubo Fan   +6 more
wiley   +1 more source

Inventory or Stockcheck?

, 2010
You have been assigned to physically count every learning resource item currently shelved in your collection. How would you respond to this seemingly impossible and intimidating task? Without a doubt, you might be overwhelmed as I was.
Womack, Jim
core   +1 more source

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source

Multivariate Contrastive Predictive Coding with Sliding Windows for Disease Prediction from Electronic Health Records

Advanced Intelligent Systems, EarlyView.
Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan, Xiaozhu Jing, Yuzheng Yan, Wuman Luo   +3 more
wiley   +1 more source

Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction

Advanced Intelligent Systems, EarlyView.
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He, Kah Phooi Seng, Chee Shen Lim, Li Minn Ang   +3 more
wiley   +1 more source