Background/Objectives: Optical coherence tomography angiography (OCTA) enables noninvasive quantitative assessment of the retinal microvasculature and is widely used in diabetic retinopathy (DR). However, OCTA-derived metrics are highly dependent on...
Document image binarization is a challenging task, especially when it comes to text segmentation in degraded document images. The binarization, as a pre-processing step of Optical Character Recognition (OCR), is one of the most fundamental and common...
In this study, we introduce an innovative policy in the field of reinforcement learning, specifically designed as an action selection mechanism, and applied herein as a selector for binarization schemes. These schemes enable continuous metaheuristics...
In this era of digitization, most hardcopy documents are being transformed into digital formats. In the process of transformation, large quantities of documents are stored and preserved through electronic scanning. These documents are available from...
Fast reconstruction of holographic and diffractive optical elements (DOE) can be implemented by binary digital micromirror devices (DMD). Since micromirrors of the DMD have two positions, the synthesized DOEs must be binary. This work studies the pos...
In order to minimize execution times, improve the quality of solutions, and address more extensive target situations, optimization techniques, particularly metaheuristics, are continually improved. Hybridizing procedures are one of these noteworthy s...
(1) Background: We aimed to reveal the relationship between the choroid and the outer retina with optical coherence tomography (OCT) in patients with diabetes mellitus (DM) with mild or no diabetic retinopathy (DR) in order to find early biomarkers f...
The Unicost Set Covering Problem (USCP), an NP-hard combinatorial optimization challenge, demands efficient methods to minimize the number of sets covering a universe. This study introduces a binary White Shark Optimizer (WSO) enhanced with V3 transf...
Metaheuristics have proven to be effective in solving large-scale combinatorial problems by combining global exploration with local exploitation, all within a reasonably short time. The balance between these phases is crucial to avoid slow or prematu...
In today’s digital age, the conversion of hardcopy documents into digital formats is widespread. This process involves electronically scanning and storing large volumes of documents. These documents come from various sources, including records...
Metaheuristics are smart problem solvers devoted to tackling particularly large optimization problems. During the last 20 years, they have largely been used to solve different problems from the academic as well as from the real-world. However, most o...
Binary neural networks (BNNs) are an extremely promising method for reducing deep neural networks’ complexity and power consumption significantly. Binarization techniques, however, suffer from ineligible performance degradation compared to thei...
For years, extensive research has been in the binarization of continuous metaheuristics for solving binary-domain combinatorial problems. This paper is a continuation of a previous review and seeks to draw a comprehensive picture of the various ways...
High-speed optical reconstruction of 3D-scenes can be achieved using digital holography with binary digital micromirror devices (DMD) or a ferroelectric spatial light modulator (fSLM). There are many algorithms for binarizing digital holograms. The m...
This article proposes a hybrid algorithm that makes use of the db-scan unsupervised learning technique to obtain binary versions of continuous swarm intelligence algorithms. These binary versions are then applied to large instances of the well-known...
In recent years, continuous metaheuristics have been a trend in solving binary-based combinatorial problems due to their good results. However, to use this type of metaheuristics, it is necessary to adapt them to work in binary environments, and in g...
Uneven illumination and space radiation can cause inhomogeneous grayscale distribution, low contrast, and noisy images in in-orbit cameras. A binarization algorithm based on morphological classification is proposed to solve the problem of inaccurate...
The Earth’s observation programs, through the acquisition of remotely sensed hyperspectral images, aim at detecting and monitoring any relevant surface change due to natural or anthropogenic causes. The proposed algorithm, given as input a pair...
Image binarization is a preprocessing technique that maps an image’s pixel values to either black or white, and it is crucial in many fields of computer vision, such as document digitization and medical imaging. Thresholding is a popular image...
The transition from continuous swarm intelligence algorithms to discrete combinatorial domains remains a critical challenge in bio-inspired computing. Traditional binarization techniques frequently induce premature convergence in highly constrained l...
The optimization methods and, in particular, metaheuristics must be constantly improved to reduce execution times, improve the results, and thus be able to address broader instances. In particular, addressing combinatorial optimization problems is cr...
Currently, an echocardiography expert is needed to identify calcium in the aortic valve, and a cardiac CT-Scan image is needed for calcium quantification. When performing a CT-scan, the patient is subject to radiation, and therefore the number of CT-...
Binary convolutional neural networks (BCNN) have shown good accuracy for small to medium neural network models. Their extreme quantization of weights and activations reduces off-chip data transfer and greatly reduces the computational complexity of c...
This paper presents a comparative study of binarization techniques for automated defect detection in dye penetrant testing (DPT) images. We evaluate established methods, including global, adaptive, and histogram-based thresholding, against three nove...
Binarized neural networks are well suited for FPGA accelerators since their fine-grained architecture allows the creation of custom operators to support low-precision arithmetic operations, and the reduction in memory requirements means that all the...
Binarization is an extreme quantization technique that is attracting research in the Internet of Things (IoT) field, as it radically reduces the memory footprint of deep neural networks without a correspondingly significant accuracy drop. To support...
The Set Coverage Problem (SCP) is an important combinatorial optimization problem known to be NP-complete. The use of metaheuristics to solve the SCP includes different algorithms. In particular, binarization techniques have been explored to adapt me...
On-road driving studies are essential for comprehending real-world driver behavior. This study investigates the use of eye-tracking (ET) technology in research on driver behavior and attention during Controlled Driving Studies (CDS). One significant...
Foam sound-absorbing materials develop a fine cellular structure during manufacturing, resulting in variations in porosity, cell size, and the proportion of naturally occurring thin membranes that obstruct skeletal openings. This membrane proportion...
This study presents a process for the quantitative investigation of thinning defects occurring in the containment liner plate (CLP) of a nuclear power plant according to various depths with a combined thermal wave signal and image processing in a loc...
The development of neutron imaging facilities provides a growing range of applications in different research fields. The significance of the obtained structural information, among others, depends on the reliability of phase segmentation. We focused o...
The aim of this work is to search for evidence of close binary stars associated with planetary nebulae (ionized stellar envelopes in expansion) by mining the astronomical archive of Gaia EDR3. For this task, using big data techniques, we selected a s...
Metaheuristics are a fundament pillar of Industry 4.0, as they allow for complex optimization problems to be solved by finding good solutions in a reasonable amount of computational time. One category of important problems in modern industry is that...
Among the non-destructive testing (NDT) techniques, infrared thermography (IRT) is an attractive and highly reliable technology that can measure the thermal response of a wide area in real-time. In this study, thinning defects in S275 specimens were...
The digitization of information and technological advancements have enabled us to gather vast amounts of data from various domains, including but not limited to medicine, commerce, and mining. Machine learning techniques use this information to impro...
Many technological applications of our time rely on images captured by multiple cameras. Such applications include the detection and recognition of objects in captured images, the tracking of objects and analysis of their motion, and the detection of...
This paper presents a methodology for rectifying curved text lines, a crucial process in optical character recognition (OCR) and computer vision. Utilizing generalized additive models (GAMs), the proposed method accurately estimates text curvature an...
Segmentation of retinal vessels plays a crucial role in detecting many eye diseases, and its reliable computerized implementation is becoming essential for automated retinal disease screening systems. A large number of retinal vessel segmentation alg...
The frequency of planets in binaries is an important issue in the field of extrasolar planet studies because of its relevance in the estimation of the global planet population of our galaxy and the clues it can give to our understanding of planet for...
The advent of 5G heralds unprecedented connectivity with high throughput and low latency for network users. Software-defined networking (SDN) plays a significant role in fulfilling these requirements. However, it poses substantial security challenges...
Maxillary second molars with root fusion exhibit considerable anatomical variability that complicates dental treatment planning. Cone-beam computed tomography (CBCT) has become an essential imaging modality for evaluating such complex morphology. Thi...
Deep learning methods have exhibited the great capacity to process object detection tasks, offering a practical and viable approach in many applications. When researchers have advanced deep learning models to improve their performance, the model deri...
A methodology for the measurement of height in water reservoirs is developed. It is based on Sentinel 2 imagery and aerial LiDAR data. The methodology is automatized using Matlab software and focused on image processing techniques (equalization, bina...
Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vec...
Wolf–Rayet stars (WRs) represent the end of a massive star’s life as it is about to turn into a supernova. Obtaining complete samples of such stars across a large range of metallicities poses observational challenges, but presents us with...
When we face real problems using computational resources, we understand that it is common to find combinatorial problems in binary domains. Moreover, we have to take into account a large number of possible candidate solutions, since these can be nume...
Nuclei segmentation is a key task in digital histopathology, highlighting important aspects of nuclear morphology and topology in many cancer-related evaluations and studies. Variability in nuclear appearance both within and across different organs,...
The main goal of this paper is to present a new way of processing a video file using a combination of multiple quantum methods. The design is built upon the novel enhanced quantum representation technique, NEQR, which is then expanded using ideas suc...
Monitoring food processing is mandatory for controlling and ensuring product quality. Most of the used techniques are destructive, arduous, and time-consuming. Non-destructive analyses are convenient for rapid and conservative food quality assessment...
This paper deals with the experimental procedures of lock-in thermography (LIT) for polyetheretherketone (PEEK), which is used as a lightweight material in various industrial fields. The LIT has limitations due to non-uniform heating by external opti...
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