Academic Articles & Research Papers

Efficient One-Dimensional Network Design Method for Underwater Acoustic Target Recognition

Many studies have used various time-frequency feature extraction methods to convert ship-radiated noise into three-dimensional (3D) data suitable for computer vision (CV) models, which have shown good results in public datasets. However, tr...

Multi-scale attention and collaborative fusion for enhanced RGB-D salient object detection in weld quality inspection

Abstract Salient object detection (SOD) plays a crucial role in computer vision by mimicking human visual attention to identify and segment the most prominent objects in a scene. The advent of depth sensing technologies has propelled RGB-D ...

Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems

Monitoring and understanding fish behavior is crucial for achieving precision in everyday husbandry practices (i.e. for optimizing farm performance), and for improving fish welfare in aquaculture. Various intelligent monitoring and control ...

Enhanced Skin Condition Prediction Through Machine Learning Using Dynamic Training and Testing Augmentation

In recent years, deep learning has taken the spotlight in automated medical bioimaging. However, the performance of current state-of-the-art score stems primarily from well-tuned parameters and architecture. There is still only limited rese...

Potential of machine learning approaches for predicting mechanical properties of spruce wood in the transverse direction

Abstract To predict the mechanical properties of wood in the transverse direction, this study used machine learning to extract the anatomical features of wood from cross-sectional stereograms. Specimens with different orientations of the ra...

Hard exudate segmentation in retinal image with attention mechanism

Abstract Diabetic retinopathy (DR) is the main reason that causes preventable blindness. Hard exudate is one of the earliest signs of diabetic retinopathy. Precise detection of hard exudate is helpful for the early diagnosis of diabetic ret...

An Efficient Optimization Technique for Training Deep Neural Networks

Deep learning is a sub-branch of artificial intelligence that acquires knowledge by training a neural network. It has many applications in the field of banking, automobile industry, agriculture, and healthcare industry. Deep learning has pl...

Euclid Quick Data Release (Q1)

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust a...

LeafNST: an improved data augmentation method for classification of plant disease using object-based neural style transfer

Abstract Plant diseases significantly threaten global agriculture, impacting crop yield and food security. Nearly 30% of the crop yield is lost due to plant diseases. Efficient identification and classification of plant diseases through com...

Enhanced gradient learning for deep neural networks

Abstract Deep neural networks have achieved great success in both computer vision and natural language processing tasks. How to improve the gradient flows is crucial in training very deep neural networks. To address this challenge, a gradie...

Non-Sinusoidal micro-Doppler Estimation Based on Dual-Branch Network

The fine state of targets can be represented by the extracted micro-Doppler (m-D) components from the radar echo. However, current methods do not consider the specialty of the m-D components, and their performance with non-sinusoidal compon...

Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM

Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, on...

A Guide to Convolutional Neural Networks for Computer Vision

A review of convolutional neural networks in computer vision

Abstract In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of dee...

Secured Perimeter with Electromagnetic Detection and Tracking with Drone Embedded and Static Cameras

Perimeter detection systems detect intruders penetrating protected areas, but modern solutions require the combination of smart detectors, information networks and controlling software to reduce false alarms and extend detection range. The ...

Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution

The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by under...

RELAX Perinatal Digital Intervention to Prevent Increasing Anxiety: A Randomized Clinical Trial.

Using different computing systems to solve the automatic cloud classification problem according to MODIS satellite data by probabilistic neural network

The relevance of the research is caused by the necessity to develop algorithms and software to classify the cloud types based on single-layer cloud on the satellite images received from MODIS spectral radiometer used in Terra and Aqua remot...

ALGORITMO PARA O RECONHECIMENTO DE CARACTERES MANUSCRITOS

The handwritten character recognition in digital images is an important and challenging area of study in Computer Vision, with several possibilities for applications to facilitate the daily work of the people. This paper presents an alg...

Architectural Framework to Enhance Image-Based Vehicle Positioning for Advanced Functionalities

The growing number of vehicles on the roads has resulted in several challenges, including increased accident rates, fuel consumption, pollution, travel time, and driving stress. However, recent advancements in intelligent vehicle technologi...