AIMC Topic: Neural Networks, Computer

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Interpreting deep neural networks for the prediction of translation rates.

BMC genomics
BACKGROUND: The 5' untranslated region of mRNA strongly impacts the rate of translation initiation. A recent convolutional neural network (CNN) model accurately quantifies the relationship between massively parallel synthetic 5' untranslated regions ...

Fusing global context with multiscale context for enhanced breast cancer classification.

Scientific reports
Breast cancer is the second most common type of cancer among women. Prompt detection of breast cancer can impede its advancement to more advanced phases, thereby elevating the probability of favorable treatment consequences. Histopathological images ...

Advancing mango leaf variant identification with a robust multi-layer perceptron model.

Scientific reports
Mango, often regarded as the "king of fruits," holds a significant position in Bangladesh's agricultural landscape due to its popularity among the general population. However, identifying different types of mangoes, especially from mango leaves, pose...

Enhancing streamflow prediction in a mountainous watershed using a convolutional neural network with gridded data.

Environmental science and pollution research international
In this research, we demonstrate the effectiveness of a convolutional neural network (CNN) model, integrated with the ERA5-Land dataset, for accurately simulating daily streamflow in a mountainous watershed. Our methodology harnesses image-based inpu...

GMOPNet: A GAN-MLP two-stage network for optical properties measurement of kiwifruit and peaches with spatial frequency domain imaging.

Food chemistry
Spatial frequency domain imaging (SFDI) is an imaging technique using spatially modulated illumination for measurement of optical properties. Conventional SFDI methods require capturing at least six images, making it time-consuming. This study presen...

A bio-inspired visual collision detection network integrated with dynamic temporal variance feedback regulated by scalable functional countering jitter streaming.

Neural networks : the official journal of the International Neural Network Society
In pursuing artificial intelligence for efficient collision avoidance in robots, researchers draw inspiration from the locust's visual looming-sensitive neural circuit to establish an efficient neural network for collision detection. However, existin...

Statistical inference and neural network training based on stochastic difference model for air pollution and associated disease transmission.

Journal of theoretical biology
A polluted air environment can potentially provoke infections of diverse respiratory diseases. The development of mathematical models can study the mechanism of air pollution and its effect on the spread of diseases. The key is to characterize the in...

A multi-layer neural network approach for the stability analysis of the Hepatitis B model.

Computational biology and chemistry
In the present study, we explore the dynamics of Hepatitis B virus infection, a significant global health issue, through a newly developed dynamics system. This model is distinguished by its inclusion of asymptomatic carriers and the impact of vaccin...

Deep-GB: A novel deep learning model for globular protein prediction using CNN-BiLSTM architecture and enhanced PSSM with trisection strategy.

IET systems biology
Globular proteins (GPs) play vital roles in a wide range of biological processes, encompassing enzymatic catalysis and immune responses. Enzymes, among these globular proteins, facilitate biochemical reactions, while others, such as haemoglobin, cont...

Artificial intelligence-enhanced infrared thermography as a diagnostic tool for thyroid malignancy detection.

Annals of medicine
INTRODUCTION: Thyroid nodules are common, and investigation is crucial for excluding malignancy. Increased intranodular vascularity is frequently observed in malignant tumors, which can be detected through increased skin surface temperatures using no...