This study systematically reviews CNN-based medical image classification methods. We
surveyed 149 of the latest and most important papers published to date and conducted an in …

Capturing global and subtle discriminative information using attention mechanisms is
essential to address the challenge of inter-class high similarity for vehicle re-identification …

The introduction of trust-based approaches in social scenarios modeled as multi-agent
systems (MAS) has been recognized as a valid solution to improve the effectiveness of these …

Brain tumors are nonlinear and present with variations in their size, form, and textural
variation; this might make it difficult to diagnose them and perform surgical excision using …

Deep Feedforward Neural Networks (FNNs) with skip connections have revolutionized
various image recognition tasks. In this paper, we propose a novel architecture called …

The pavement skid resistance is crucial for ensuring driving safety. However, the
reproducibility and comparability of field measurements are constrained by various …

In many modern machine learning models, attention mechanisms play a crucial role in
processing data and identifying significant parts of the inputs, whether these are text or …

The 3D point cloud deep neural network (3D DNN) has achieved remarkable success, but
its black-box nature hinders its application in many safety-critical domains. The saliency map …

Event-based cameras are novel sensors that capture asynchronous changes in brightness
with high temporal resolution. The output of an event camera is called an event. Events are a …

Betula luminifera, an indigenous hardwood tree in South China, possesses significant
economic and ecological value. In view of the current severe drought situation, it is urgent to …