With the rapid advancements in the field of autonomous driving, the need for faster and more
accurate object detection frameworks has become a necessity. Many recent deep learning …

Recent deep learning-based object detectors have shown compelling performance for the
detection of large objects in autonomous driving applications. However, the detection of …

Convolutional neural networks (CNNs) have successfully driven many visual recognition
tasks including image classification. However, when dealing with classification tasks with …

Visual pattern recognition, selection of appropriate image processing techniques, and
network architecture are key factors in achieving optimal model performance. This article …

With the development of autonomous vehicles and intelligent transportation, more accurate
detection of pedestrians. However, pedestrian detection suffers from occlusion and small …

The mesoscale eddies are prevalent oceanic circulation phenomena, exerting significant
influence on various aspects of the marine environment including energy transfer, material …

Ship classification, as an important problem in the field of computer vision, has been the
focus of research for various algorithms over the past few decades. In particular …

Aim: Up to date many successful attempts to identify various types of lesions with machine
learning (ML) were made, however, the recognition of Alzheimer's disease (AD) from brain …

This research investigates the use of deep learning for diagnosing lung diseases like
Chronic Obstructive Pulmonary Disease (COPD) using Chest X-rays (CXR). The study …

The perceptual scope of deep convolutional neural networks is inherently confined to a local
scale due to the inherent limitations of convolution operations. This confinement …