High aspect ratio microstructures (HARMS) are of great importance for many application fields. Many defects are generated during the fabrication processes, especially in line microstructures, and it is necessary to examine the quality of the structur...
The rapid spread of misinformation threatens public safety and social stability. Although deep learning-based detection methods have achieved promising results, their effectiveness heavily relies on large amounts of labeled data, limiting their appli...
This paper considers the active detection of a stealth target with aspect dependent reflection (e.g., submarine, aircraft, etc.) using wireless sensor networks (WSNs). When the target is detected, its localization is also of interest. Due to stringen...
Object detection is a significant and challenging problem in the study area of remote sensing and image analysis. However, most existing methods are easy to miss or incorrectly locate objects due to the various sizes and aspect ratios of objects. In...
Object detection is a significant and challenging problem in the study of remote sensing. Since remote sensing images are typically captured with a bird’s-eye view, the aspect ratios of objects in the same category may obey a Gaussian distribution. G...
Multi-aspect synthetic aperture radar (SAR) images contain more information available for automatic target recognition (ATR) than images from a single view. However, the sensitivity to aspect angles also makes it hard to extract and integrate informa...
Drowsiness is a major risk factor for road safety, contributing to serious injury, death, and economic loss on the road. Driving performance decreases because of increased drowsiness. In several different applications, such as facial movement analysi...
The accurate identification of pulmonary nodules is critical for the early diagnosis of lung diseases; however, this task remains challenging due to inadequate feature representation and limited localization sensitivity. Current methodologies often u...
Object detection in remote sensing imagery plays a pivotal role in various applications, including aerial surveillance and urban planning. Despite its significance, the task remains challenging due to cluttered backgrounds, the arbitrary orientations...
Currently, the number of vehicles in circulation continues to increase steadily, leading to a parallel increase in vehicular accidents. Among the many causes of these accidents, human factors such as driver drowsiness play a fundamental role. In this...
Advancements in text representation have produced many deep language models (LMs), such as Word2Vec and recurrent-based LMs. However, there are scarce works that focus on detecting implicit sentiments with a small amount of labelled data because ther...
Aspect-based sentiment analysis (ABSA) is a method used to identify the aspects discussed in a given text and determine the sentiment expressed towards each aspect. This can help provide a more fine-grained understanding of the opinions expressed in...
All kinds of vehicles have different ratios of width to height, which are called the aspect ratios. Most previous works, however, use a fixed aspect ratio for vehicle detection (VD). The use of a fixed vehicle aspect ratio for VD degrades the perform...
This article covers the issues of constructing tools for detecting network attacks targeting devices in IoT clouds. The detection is performed within the framework of cloud infrastructure, which receives data flows that are limited in size and conten...
Convolutional neural networks (CNNs) have demonstrated their ability object detection of very high resolution remote sensing images. However, CNNs have obvious limitations for modeling geometric variations in remote sensing targets. In this paper, we...
Car accidents remain a leading cause of death worldwide, with drowsiness and distraction accounting for roughly 25% of fatal crashes in Ecuador. This study presents a real-time driver monitoring system that uses computer vision and deep learning to d...
Logo detection is a technology that identifies logos in images and returns their locations. With logo detection technology, brands can check how often their logos are displayed on social media platforms and elsewhere online and how they appear. It ha...
Drowsiness-related car accidents continue to have a significant effect on road safety. Many of these accidents can be eliminated by alerting the drivers once they start feeling drowsy. This work presents a non-invasive system for real-time driver dro...
Multimodal sentiment analysis (MSA) has attracted growing interest among researchers in recent years, as multimodal user-generated content (e.g., text and images) has become increasingly common on the Internet. In Aspect-Based Sentiment Analysis (ABS...
The characteristics of multi-directional rotation and high aspect ratio of targets such as shipwrecks lead to low detection accuracy and difficulty localizing existing detection models for this target type. Through our research, we design three main...
Sentiment analysis has increasingly gained significance in commercial settings, driven by the rising impact of reviews on purchase decision-making in recent years. This research conducts a thorough examination of the suitability of machine learning a...
Governments these days are demanding better Smart City technologies in order to connect with citizens and understand their demands. For such governments, much needed information exists on social media where members belonging to diverse groups share d...
Smart security based on object detection is one of the important applications of edge computing in IoT. Anchors in object detection refer to points on the feature map, which can be used to generate anchor boxes and serve as training samples. Current...
Detecting the main aspects of a particular product from a collection of review documents is so challenging in real applications. To address this problem, we focus on utilizing existing topic models that can briefly summarize large text documents. Unl...
The emergence of advanced machine learning or deep learning techniques such as autoencoders and generative adversarial networks, can generate images known as deepfakes, which astonishingly resemble the realistic images. These deepfake images are hard...
Oriented object detection in remote sensing images has achieved substantial progress, yet non-maximum suppression (NMS) remains vulnerable to angular variation when the overlap of high-aspect-ratio objects is measured with rotated bounding boxes. To...
Generally, the interesting objects in aerial images are completely different from objects in nature, and the remote sensing objects in particular tend to be more distinctive in aspect ratio. The existing convolutional networks have equal aspect ratio...
Landslide identification is a fundamental step enabling the assessment of landslide susceptibility and determining the associated risks. Landslide identification by conventional methods is often time-consuming, therefore alternative techniques, inclu...
Multi-label text classification is a fundamental and important task in natural language processing, with widespread applications in specialized domains such as sentiment analysis, legal document classification, and medical coding. However, real-world...
Driver drowsiness detection systems are often evaluated using data partitions that may retain observations from the same individuals across training and testing, making their ability to generalise to unseen drivers difficult to assess. This study inv...
Multi-class oriented ship detection in optical remote sensing images remains challenging in densely berthed and nearshore scenes. Elongated hulls, arbitrary headings, background clutter, and similar vessel appearances can weaken feature aggregation a...
Current remote sensing (RS) detectors often rely on predefined anchor boxes with fixed angles to handle the multi-directional variations of targets. This approach makes it challenging to accurately select regions of interest and extract features that...
In this paper, a nanobiosensor with surface-enhanced Raman scattering (SERS) capability is introduced for highly sensitive miRNA detection in colorectal cancer. This sensor was designed and fabricated by employing a nanoshielding mechanism from nanop...
The analysis of user-generated content on the Internet has become increasingly popular for a wide variety of applications. One particular type of content is represented by the user reviews for programs, multimedia, products, and so on. Investigating...
Maintaining a healthy cyber society is a great challenge due to the users’ freedom of expression and behavior. This can be solved by monitoring and analyzing the users’ behavior and taking proper actions. This research aims to present a p...
With COVID-19, formal education was interrupted in all countries and the importance of distance learning has increased. It is possible to teach any lesson with various communication tools but it is difficult to know how far this lesson reaches to the...
The use of gold nanorods (AuNRs) as surface-enhanced Raman scattering (SERS) substrates has gained much attraction due to their remarkably aspect-ratio-dependent plasmonic properties. In this report, we described the development of AuNRs with a high...
Reliable measurement of surface roughness (Ra) is extremely important for quality control of production processes. The cost of the equipment and the duration of the measurement process are very high. The aim of this work is to develop a device for no...
This paper discusses the challenges associated with a class imbalance in medical data and the limitations of current approaches, such as machine multi-task learning (MMTL), in addressing these challenges. The proposed solution involves a novel hybrid...
Current mainstream remote sensing target detection algorithms mostly estimate the rotation angle of targets by designing different bounding box descriptions and loss functions. However, they fail to consider the symmetry–asymmetry duality aniso...
African swine fever remains one of the most economically important and dangerous diseases of the Suidae family. Until now, neither a safe vaccine nor a treatment against ASF has been available, which is why prevention of the disease involves biosecur...
Drowsiness while driving poses a significant risk in terms of road safety, making effective drowsiness detection systems essential for the prevention of accidents. Facial signal-based detection methods have proven to be an effective approach to drows...
Online reviews significantly influence consumer behavior and business reputations. Detecting fake reviews is important for maintaining trust and integrity in these platforms. We present an aspect-based sentiment analysis approach, referred to as Fake...
(1) Background: The Alberta Stroke Program Early CT Score (ASPECTS) is a standardized scoring tool used to evaluate the severity of acute ischemic stroke (AIS) on non-contrast CT (NCCT). Our aim in this study was to automate ASPECTS. (2) Methods: We...
Given that urban mobility arises from the interaction between social and environmental conditions, this study constructs a Bayesian network to represent these relationships in David, Panama, using 500 georeferenced household surveys that recorded var...
In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A
Due to the globalisation of the economy, migratory flows have increased significantly. Unaccompanied foreign minors have become a growing problem in recent years. The objective of this study is to make an analysis from a bibliometric point of view an...
27 August 2024
As blockchain technology increasingly underpins digital transactions, smart contracts have emerged as a pivotal tool for automating these transactions. While smart contracts offer efficiency and security, their automation introduces significant legal...
As there is a huge amount of information on the Internet, people have difficulty in sorting through it to find the required information; thus, the information overload problem becomes a significant issue for users and online businesses. To resolve th...
Over the past few years, target detectors that utilize Convolutional Neural Networks have gained extensive application in the domain of remote sensing (RS) imagery. Recently, optimizing bounding boxes has consistently been a hot topic in the research...
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