The diagnosis of breast cancer in the early stages significantly decreases the mortality rate
by allowing the choice of adequate treatment. This study developed and evaluated twenty …

Reinforcement Learning and recently Deep Reinforcement Learning are popular methods
for solving sequential decision making problems modeled as Markov Decision Processes …

With the advancement in pose estimation techniques, human posture detection recently
received considerable attention in many applications, including ergonomics and healthcare …

Diabetic retinopathy (DR) is the most severe ocular complication of diabetes. It leads to
serious eye complications such as vision impairment and blindness. A computer-aided …

Purpose Neuro-fuzzy systems aim to combine the benefits of artificial neural networks and
fuzzy inference systems: a neural network can learn patterns from data and achieves high …

Deep learning methods have relevant applications in crack detection in buildings. However,
one of the challenges in this field is the hyperparameter tuning process for convolutional …

Deep Learning methods have important applications in the building construction image
classification field. One challenge of this application is Convolutional Neural Networks …

Diabetic retinopathy (DR) is one of the main causes of vision loss around the world. The
early diagnosis of this disease can help in treating it efficiently. Deep learning (DL) is rapidly …

The traveling salesman problem (TSP) is one of the best-known combinatorial optimization
problems. Many methods derived from TSP have been applied to study autonomous vehicle …

Many wave energy conversion applications require future knowledge or forecasting of the
wave excitation force values. Most wave energy converter (WEC) control strategies need to …