Results 111 to 120 of about 5,685 (163)

Clinical Note Generation From Doctor-Patient Conversations Using Parameter-Efficient Fine-Tuning Large Language Models: Comparative Study. [PDF]

JMIR Med Inform
Ahmed S, Yousuf Sadeque F.
europepmc   +1 more source

Real-Time Cardiac Arrhythmia Classification Using TinyML on Ultra-Low-Cost Microcontrollers: A Feasibility Study for Resource-Constrained Environments. [PDF]

Bioengineering (Basel)
Zambrano-de la Torre M, Guzman-Alfaro S, Acuña-Correa A, Soto-Murillo MA, Guzmán-Fernández M, Robles-Ortiz R, Villagrana-Bañuelos KE, Arceo-Olague JG, Espino-Salinas CH, Sánchez-Reyna AG, Cuevas-Rodriguez EO.   +10 more
europepmc   +1 more source

Exploring the feasibility of real-time on-device ECG biometric classification using quantized neural networks. [PDF]

Front Digit Health
Berki M, Mateasik A, Micjan M, Vavrinsky E, Gasparek K, Cernaj L.   +5 more
europepmc   +1 more source

Neuromorphic spike-based large language model. [PDF]

Natl Sci Rev
Xu H, Qiu X, Xu Y, Elbtity ME, Zhou P, Tian Y, Zhu RJ, Zhang J, Gu S, Pan Y, Chou Y, Wen Q, Yao M, Qian J, Tian Y, Ma L, Huang T, Eshraghian JK, Xu B, Li G.   +19 more
europepmc   +1 more source

MedPTQ: a practical pipeline for real post-training quantization in 3D medical image segmentation. [PDF]

J Med Imaging (Bellingham)
Qu C, Zhao R, Yu Y, Liu B, Yao T, Zhu J, Landman BA, Tang Y, Huo Y.   +8 more
europepmc   +1 more source

Balancing accuracy and efficiency: co-design of hybrid quantization and unified computing architecture for spiking neural networks. [PDF]

Front Neurosci
Li J, Xu M, Dong H, Lan B, Liu Y, Chen H, Zhuang Y, Xie Y, Chen L.   +8 more
europepmc   +1 more source

High-Payload and Secure Data Hiding for Medical Images in IoMT-Based eHealth Systems. [PDF]

Sensors (Basel)
Wang Y, Lin Y, Chang CC, Chang CC, Hwang WY.   +4 more
europepmc   +1 more source

Adaptive one-bit quantization for compressed sensing [PDF]

Signal Processing, 2016
There have been a number of studies on sparse signal recovery from one-bit quantized measurements. Nevertheless, less attention has been paid to the choice of the quantization thresholds and its impact on the signal recovery performance. In this paper, we examine the problem of quantization in a general framework of one-bit compressed sensing with non ...
Jun Fang, Linxiao Yang, Yanning Shen
exaly   +2 more sources

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Optimum one-bit quantization

2015 IEEE Information Theory Workshop - Fall (ITW), 2015
This paper deals with discrete input one-bit output quantization. A discrete input signal is subject to additive noise and is then quantized to zero or one by comparison with a threshold q. For finitely many fixed support points and fixed threshold q we first determine the mutual information of this channel. The capacity-achieving input distribution is
Gholamreza Alirezaei, Rudolf Mathar
openaire   +1 more source