Brain tumor segmentation from MRIs has always been a challenging task for radiologists,
therefore, an automatic and generalized system to address this task is needed. Among all …

Secondary metabolites made by plants and used through their metabolic routes are today's
most reliable and cost-effective way to make pharmaceuticals and improve health. The …

Abstract Machine-learning techniques are discovering effective performance on data
analytics. Classification and regression are supported for prediction on different kinds of …

Background The advent of deep learning technologies has expanded the utilization of
convolutional neural networks in diagnosing and segmenting plant leaf diseases. However …

This research study compares the accuracy of different techniques based on deep learning
(DL) for predicting turbulent flows. Different types of Generative Adversarial Networks …

Accurate and robust collection of plant phenotypic data offers theoretical as well as technical
support to support the growth of crop science and to ensure ecological security, agricultural …

Breast cancer is a diverse female malignancy; its classification is based on clinical evidence
and pathological elucidation. Large public drug screening data databases combined with …

Objective. This study is aimed at exploring the impact of eye model based on multichannel
convolutional neural network (CNN) on eye plastic surgery and aesthetic effect, thus …

A series of multidrug extransporters known as the multidrug and potentially toxic extrusion
(MATE) genes are found in all living things and are crucial for the removal of heavy metal …

Although a strategy for predicting stock prices using relational data has been described
recently, no practical way for selecting aggregating various forms of relational data to …