AIMC Topic: Neural Networks, Computer

Clear Filters Showing 291 to 300 of 31376 articles

A rapid wine brand identification method based on the joint application of SERS and machine learning techniques.

Food chemistry
In this paper, an innovative approach is proposed to achieve no-preparation, rapid, and accurate identification of red wine brands by combining Surface-Enhanced Raman Scattering (SERS) spectroscopy with machine learning. SERS detects trace molecular ...

Deep Fuzzy-NN modeling for the prediction of Zn(II) adsorption in columns using alkaline modified biochar: Integrated experimental and computational insights.

Environmental research
The precise prediction of adsorption process is significant in the optimization of pollutant removal systems. In this research, deep fuzzy neural network (DFNN) model was developed for the prediction of Zn(II) removal efficiency using alkaline activa...

A novel approach integrating topological deep learning from EEG Data in Alzheimer's disease.

Scientific reports
High-throughput analysis of EEG data has significantly contributed to understanding neural dynamics in Alzheimer's disease diagnosis. However, the complexity and high dimensionality of EEG signals pose challenges for traditional classification method...

Named Entity Recognition for Chinese Cancer Electronic Health Records-Development and Evaluation of a Domain-Specific BERT Model: Quantitative Study.

JMIR medical informatics
BACKGROUND: The unstructured data of Chinese cancer electronic health records (EHRs) contains valuable medical expertise. Accurate medical entity recognition is crucial for building a medical-assisted decision system. Named entity recognition (NER) i...

TF-crossnet: a cross-modal attention fusion network for cardiovascular disease classification using pcg and ecg signals.

Biomedical physics & engineering express
Electrocardiogram (ECG) and phonocardiogram (PCG) have emerged as crucial non-invasive and portable diagnostic modalities for early cardiovascular disease (CVD) screening. Despite the individual merits of these signal modalities in CVD detection, sig...

Deepfake defense: Combining spatial and temporal cues with CNN-BiLSTM-transformer architecture.

PloS one
The proliferation of deepfakes is a major threat to the believability of online media and the stability of public discourse. These hyper-realistic fake videos, nearly indistinguishable from genuine content, can be misused to spread disinformation, co...

Enhanced multi-horizon photovoltaic power forecasting: A novel approach integrating ICEEMDAN decomposition with hierarchical frequency neural networks.

PloS one
As a crucial renewable energy source, solar PV power generation drives environmental protection and energy transformation. However, existing forecasting models struggle to accurately capture the complex dynamics of photovoltaic (PV) power, primarily ...

Recognition method of bridge apparent defects based on image processing and improved convolutional neural networks.

PloS one
As an important transportation hub, the detection of appearance defects in bridges has been characterized by low accuracy and low efficiency. To address this problem, the study proposes a bridge appearance defect recognition model based on image proc...

Research on the Identification of Composite Spices Based on Terahertz Spectroscopy and Machine Learning Algorithms.

Journal of food protection
The similar appearance and composition of pungent spices frequently give rise to adulteration, which not only causes market confusion but also results in inconsistent product quality. This study employed terahertz time-domain spectra and absorption s...

Emergent neuronal mechanisms mediating covert attention in convolutional neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Covert visual attention allows the brain to select different regions of the visual world without eye movements. Predictive cues of a target location orient covert attention and improve perceptual performance. In most computational models, researchers...