[HTML][HTML] Revolutionizing digital pathology with the power of generative artificial intelligence and foundation models
Digital pathology has transformed the traditional pathology practice of analyzing tissue
under a microscope into a computer vision workflow. Whole slide imaging allows …
under a microscope into a computer vision workflow. Whole slide imaging allows …
[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
A new hybrid based on long short-term memory network with spotted hyena optimization algorithm for multi-label text classification
H Khataei Maragheh, FS Gharehchopogh… - Mathematics, 2022 - mdpi.com
An essential work in natural language processing is the Multi-Label Text Classification
(MLTC). The purpose of the MLTC is to assign multiple labels to each document. Traditional …
(MLTC). The purpose of the MLTC is to assign multiple labels to each document. Traditional …
Multi-domain modeling of atrial fibrillation detection with twin attentional convolutional long short-term memory neural networks
Atrial fibrillation (AF) is a common arrhythmia, and its incidence increases with age. Many
methods have been developed to identify AF, including both the hand-picked features by …
methods have been developed to identify AF, including both the hand-picked features by …
A novel complex-valued convolutional neural network for medical image denoising
Several applications of complex-valued networks have been reported for computer vision
tasks like image processing and classification. However, complex-valued convolutional …
tasks like image processing and classification. However, complex-valued convolutional …
Ultrasonic thyroid nodule detection method based on U-Net network
C Chu, J Zheng, Y Zhou - Computer Methods and Programs in Biomedicine, 2021 - Elsevier
Objective Aiming at the time consuming processing of existing thyroid nodule detection and
difficulty in feature extraction, U-Net-based thyroid nodule detection is proposed to perform …
difficulty in feature extraction, U-Net-based thyroid nodule detection is proposed to perform …
[HTML][HTML] 基于卷积神经网络的井中分布式光纤传感器地震数据随机噪声压制新技术
董新桐， 李月， 刘飞， 冯黔堃， 钟铁 - 地球物理学报, 2021 - html.rhhz.net
分布式光纤传感器(distributed fiber-optical acoustic sensor, DAS) 是一种快速发展的具有巨大
应用前景的地震勘探检波器技术. 实际DAS 地震资料往往会受到大量强能量随机噪声的干扰 …
应用前景的地震勘探检波器技术. 实际DAS 地震资料往往会受到大量强能量随机噪声的干扰 …
[HTML][HTML] Performance evaluation of metaheuristics-tuned recurrent neural networks for electroencephalography anomaly detection
D Pilcevic, M Djuric Jovicic, M Antonijevic… - Frontiers in …, 2023 - frontiersin.org
Electroencephalography (EEG) serves as a diagnostic technique for measuring brain waves
and brain activity. Despite its precision in capturing brain electrical activity, certain factors …
and brain activity. Despite its precision in capturing brain electrical activity, certain factors …
Simulation of karst spring discharge using a combination of time–frequency analysis methods and long short-term memory neural networks
Spring discharges from karst aquifers are results of spatially and temporally complex
hydrologic processes, such as precipitation, surface runoff, infiltration, groundwater flow as …
hydrologic processes, such as precipitation, surface runoff, infiltration, groundwater flow as …
Anomaly detection and prediction in discrete manufacturing based on cooperative LSTM networks
B Lindemann, N Jazdi… - 2020 IEEE 16th …, 2020 - ieeexplore.ieee.org
Manufacturing processes are characterized by their temporal and spatial distributed
nonlinear physics. Analytical models are not available and numerical models do not …
nonlinear physics. Analytical models are not available and numerical models do not …