Academic Articles & Research Papers

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathol...

Determination of optimum segmentation parameter values for extracting building from remote sensing images

Lately, with progresses in remote sensing information techniques and the growingly and unprecedented uses of its uses, remote sensing became a science that cannot be dispensed with in most fields and ground object extraction has turned out ...

Xylan Is Critical for Proper Bundling and Alignment of Cellulose Microfibrils in Plant Secondary Cell Walls

Plant biomass represents an abundant and increasingly important natural resource and it mainly consists of a number of cell types that have undergone extensive secondary cell wall (SCW) formation. These cell types are abundant in the stems ...

Image Analysis in Plant Sciences: Publish Then Perish

An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data

In France, in the peri-urban context, urban sprawl dynamics are particularly strong with huge population growth as well as a land crisis. The increase and spreading of built-up areas from the city centre towards the periphery takes place to...

Analysis of Multi Temporal Satellite Imagery for Total Suspended Sediments in a Wave-Active Coastal Area-Gaza Strip Coastal Water, Palestine

Sediment load materials is one of the key factors that determine the surface water quality, both of oceanic and river water, and it specifies water optical properties. Thus it provides a background for a plenty of applications and project...

An Evidence Theoretic Approach for Traffic Signal Intrusion Detection

The increasing attacks on traffic signals worldwide indicate the importance of intrusion detection. The existing traffic signal Intrusion Detection Systems (IDSs) that rely on inputs from connected vehicles and image analysis techniques can...

A Framework to Estimate the Nutritional Value of Food in Real Time Using Deep Learning Techniques

There has been a rapid increase in dietary ailments during the last few decades, caused by unhealthy food routine. Mobile-based dietary assessment systems that can record real-time images of the meal and analyze it for nutritional content c...

The estimation of canopy attributes from digital cover photography by two different image analysis methods

Proximal sensing methods using digital photography have gained wide acceptance for describing and quantifying canopy properties. Digital hemispherical photography (DHP) is the most widely used photographic technique for canopy description. ...

Geographic Object-Based Image Analysis Framework for Mapping Vegetation Physiognomic Types at Fine Scales in Neotropical Savannas

Regional maps of vegetation structure are necessary for delineating species habitats and for supporting conservation and ecological analyses. A systematic approach that can discriminate a wide range of meaningful and detailed vegetation cla...

Introduction to Mathematical Morphology

For the purposes of image analysis and pattern recognition, one often transforms an image into another better represented form. Image-processing techniques have been developed tremendously during the past ve decades and mathematical morphol...

MOMENTS OF THE LENGTH OF LINE SEGMENTS IN HOMOGENEOUS PLANAR STIT TESSELLATIONS

Homogeneous planar tessellations stable under iteration (STIT tessellations) are considered. Using recent results about the joint distribution of direction and length of the typical I-, K- and J-segment we prove closed formulas for the firs...

Data Mining Techniques in Medical Informatics

The advent of high-performance computing has benefited various disciplines in finding practical solutions to their problems, and our health care is no exception to this.Signal processing, image processing, and data mining tools have been de...

Medical Informatics: An Introduction

1. Information Processing in Medicine.- 1.1 Introduction.- 1.2 Overlap With Other Disciplines.- 2. Informatics.- 2.1 Structure.- 2.2 Fundamental Concepts.- 2.2.1 Message and Information.- 2.2.1.1 Events, Probability.- 2.2.1.2 SHANNON'S Info...

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Purpose: The goals of this study were to assess the performance of a novel lesion segmentation tool for longitudinal analyses, as well as to validate the generated lesion progression map between two time points using conventional and non-co...

The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review

Abstract Nowadays, machine learning (ML) has attained a high level of achievement in many contexts. Considering the significance of ML in medical and bioinformatics owing to its accuracy, many investigators discussed multiple solutions for ...

The Role of Cone-Beam Computed Tomography CT Extremity Arthrography in the Preoperative Assessment of Osteoarthritis

Osteoarthritis (OA) is a prevalent disease and the leading cause of pain, disability, and quality of life deterioration. Our study sought to evaluate the image quality and dose of cone-beam computed tomography arthrography (CBCT-A) and comp...

Fundus imaging based quantum computing: Grading of severity of vision threatening diabetic retinopathy

Diabetic Retinopathy (DR) is a major complication of diabetes that can result in irreversible vision loss if not detected early. Manual ophthalmologic screening is time-consuming and subject to subjectivity, underscoring the need for accura...

Using an Inspired Quantum-Classical Sequential Neural Network to Segment Liver Tumor Images Accurately

Medical analytics based on multimodal intelligence are essential to contemporary healthcare, especially in the diagnosis and detection of liver cancer. However, low contrast, varied textures, and irregular tumor forms in medical imaging con...

A survey of uncertainty in deep neural networks

Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...