Computational intelligence and neuroscience
Oct 26, 2020
In the paper, the flight time deviation of Lithuania airports has been analyzed. The supervised machine learning model has been implemented to predict the interval of time delay deviation of new flights. The analysis has been made using seven algorit...
Quantification of phenotypic heterogeneity present amongst bacterial cells can be a challenging task. Conventionally, classification and counting of bacteria sub-populations is achieved with manual microscopy, due to the lack of alternative, high-thr...
Computer methods and programs in biomedicine
Oct 25, 2020
BACKGROUND AND OBJECTIVES: Despite recent advances in artificial intelligence for medical images, the development of a robust deep learning model for identifying malignancy on pathology slides has been limited by problems related to substantial inter...
PURPOSE: To perform an in-depth evaluation of current state of the art techniques in training neural networks to identify appropriate approaches in small datasets.
New ongoing rural construction has resulted in an extensive mixture of new settlements with old ones in the rural areas of China. Understanding the spatial characteristic of these rural settlements is of crucial importance as it provides essential in...
Ulcerative colitis is a type of inflammatory bowel disease characterized by chronic and recurrent nonspecific inflammation of the intestinal tract. To find susceptibility genes and develop a novel predictive model of ulcerative colitis, two sets of c...
Early fault detection in squirrel cage induction motor (SCIM) can minimize the downtime and maximize production. This paper presents an adaptive gradient optimizer based deep convolutional neural network (ADG-dCNN) technique for bearing and rotor fau...
Electromagnetic fields (EMF) can generate reactive oxygen species and induce oxidative modifications. We investigated the effects of extremely low-frequency electromagnetic fields (ELF-EMF) on oxidative status of plasma and erythrocytes in β-thalasse...
PURPOSE: Suspected fractures are among the most common reasons for patients to visit emergency departments and often can be difficult to detect and analyze them on film scans. Therefore, we aimed to design a Deep Learning-based tool able to help doct...
In this paper, two novel, powerful, and robust convolutional neural network (CNN) architectures are designed and proposed for two different classification tasks using publicly available data sets. The first architecture is able to decide whether a gi...
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