AIMC Topic: Neural Networks, Computer

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Intelligent Recognition of Goji Berry Pests Using CNN With Multi-Graphic-Occlusion Data Augmentation and Multiple Attention Fusion Mechanisms.

Archives of insect biochemistry and physiology
Goji berry is an important economic crop, yet pest infestations pose a significant threat to its yield and quality. Traditional pest identification mainly relies on manual inspection by experts with specialized knowledge, which is subjective, time-co...

Pyrolysis mechanism study on xylose by combining experiments, chemical reaction neural networks and density functional theory.

Bioresource technology
Chemical reaction neural networks (CRNN) and density functional theory (DFT) are gaining attention in biomass pyrolysis mechanism research. Reaction pathways are often speculated based on a single method, influenced by expert knowledge. To address th...

pACPs-DNN: Predicting anticancer peptides using novel peptide transformation into evolutionary and structure matrix-based images with self-attention deep learning model.

Computational biology and chemistry
Globally, cancer remains a major health challenge due to its high mortality rates. Traditional experimental approaches and therapies are resource-intensive and often cause significant side effects. Anticancer peptides (ACPs) have emerged as alternati...

Lung cancer detection and classification using optimized CNN features and Squeeze-Inception-ResNeXt model.

Computational biology and chemistry
Lung cancer, with its high mortality rate, is one of the deadliest diseases globally. The alarming increase in lung cancer deaths and its widespread prevalence have led to the development of various cancer control research and early detection methods...

Fingerprinting of Boletus bainiugan: FT-NIR spectroscopy combined with machine learning a new workflow for storage period identification.

Food microbiology
Food authenticity and food safety issues have threatened the prosperity of the entire community. The phenomenon of selling porcini mushrooms as old mixed with new jeopardizes consumer safety. Herein, nucleoside contents and spectra of 831 Boletus bai...

PocketDTA: A pocket-based multimodal deep learning model for drug-target affinity prediction.

Computational biology and chemistry
Drug-target affinity prediction is a fundamental task in the field of drug discovery. Extracting and integrating structural information from proteins effectively is crucial to enhance the accuracy and generalization of prediction, which remains a sub...

A small-scale data driven and graph neural network based toxicity prediction method of compounds.

Computational biology and chemistry
Toxicity prediction is crucial in drug discovery, helping identify safe compounds and reduce development risks. However, the lack of known toxicity data for most compounds is a major challenge. Recently, data-driven models have gained attention as a ...

A novel intelligent framework for assessing within-host transmission dynamics of Chikungunya virus using an unsupervised stochastic neural network approach.

Computational biology and chemistry
In this study, we present a novel intelligent computing framework based on unsupervised random projection neural networks for analyzing the within-host transmission dynamics of the Chikungunya virus with an adaptive immune response. In addition to th...

Simultaneous detection of citrus internal quality attributes using near-infrared spectroscopy and hyperspectral imaging with multi-task deep learning and instrumental transfer learning.

Food chemistry
Simultaneous determination of multiple quality attributes of citrus fruits using hyperspectral imaging (HSI) and near-infrared (NIR) spectroscopy and successfully transferring the models among different instruments are two main challenges. In this st...