This paper investigates the classification of radiographic images with eleven convolutional
neural network (CNN) architectures (GoogleNet, VGG-19, AlexNet, SqueezeNet, ResNet-18 …

With each passing year, the consumption of electric energy in Brazil and the world
increases, making it necessary to adopt measures such as the construction of new plants …

A leading cause of irreversible vision loss, glaucoma needs early detection for effective
management. Intraocular Pressure (IOP) is a significant risk factor for glaucoma …

Knowledge of a person's level of skin pigmentation, or so-called “skin tone”, has proven to
be an important building block in improving the performance and fairness of various …

This work focuses on building a price prediction system by combining product images and
product properties. The intent is to find the performance of these models on single and multi …

In the field of pediatric orthopedics, accurate and timely identification of wrist fractures is vital
for effective treatment and recovery. Fractures significantly affect daily activities and can lead …

Robust anomaly detection algorithm is critical to a significant number of applications. Deep
Neural Network can resolve this problem with the good accuracy. This paper demonstrates …

Computer-aided detection of anomalies in X-ray images is of great importance and is one of
the important branches of image recognition. This study aims to develop DenseNet, a deep …