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Topic Review
Object Detection of Remote Sensing Image
Remote sensing image object detection tasks play a pivotal role in the realm of airborne and satellite remote sensing imagery, representing invaluable applications. Remote sensing technology has witnessed remarkable progress, enabling the capture of copious details that inherently reflect the contours, hues, textures, and other distinctive attributes of terrestrial targets. It has emerged as an indispensable avenue for acquiring comprehensive knowledge about the Earth’s surface. The primary objective of remote sensing image object detection is to precisely identify and locate objects of interest within the vast expanse of remote sensing images. This task finds extensive implementation across significant domains, including military reconnaissance, urban planning, environmental monitoring, soil science, and maritime vessel surveillance. With the incessant advancement of observational techniques, the availability of high-quality remote sensing image datasets, encompassing richer and more intricate information, has unlocked immense developmental potential for the ongoing pursuit of remote sensing image object detection.
  • 342
  • 23 Oct 2023
Topic Review
Recommender System for the Tourism Domain
Tourism is a widespread activity and a huge industry, in their travels, tourists have to select among numerous alternatives of landmarks, places and in general points of interest (POIs) they can visit. This can be challenging for travellers that have no prior experience of or “inside knowledge” regarding their destination, and even more so for short-term visits. As a result, a booming industry of travel-related recommender systems (RSs) has been developed, in order to provide users with recommendations most relevant to their interests. Recommender systems are considered to be personalized and non-personalized. Personalized recommender systems extrapolate user’s preferences to create efficient recommendations based on the users’ past interaction with the system. On the contrary, non-personalized recommenders suggest items that are most relevant and popular among all users.
  • 371
  • 23 Oct 2023
Topic Review
Mass Appraisal Models of Real Estate Tax Value
Artificial neural network (ANN)-based analysis can reveal differences in tax leakage loss rates in different geographical regions of countries. Experts can adjust a region’s valuation data based on property tax leakage loss rates. Appraisers can contribute to solving the problem by highlighting areas with high tax leakage loss rates and communicating their findings to valuation stakeholders, local administrators, and policymakers. This can lead to more fair and efficient tax policies that benefit the real estate sector and the economy.
  • 260
  • 23 Oct 2023
Topic Review
Traffic Pattern in Smart Cities
Smart cities have large-scale infrastructures that have been developed to monitor a wide variety of urban occurrences. This is done to improve the quality of urban life. In most instances, they place a very restricted and specific emphasis on (e.g., monitoring the traffic). They are expensive, need the management of specialists, and are not universally well-liked among residents since they focus on topics that are not (often) of public importance. 
  • 193
  • 23 Oct 2023
Topic Review
Text Emotions on Non-English Datasets
Machine learning approaches, in particular graph learning methods, have achieved great results in the field of natural language processing, in particular text classification tasks. However, many of such models have shown limited generalization on datasets in different languages. 
  • 263
  • 23 Oct 2023
Topic Review
Supervised Log Anomaly with Probabilistic Polynomial Approximation
Audit and Security log collection and storage are essential for organizations worldwide to recognize security breaches and are required by law. Logs often contain sensitive information about an organization or its customers. Fully Homomorphic Encryption (FHE) allows calculations on encrypted data, thus very useful for privacy-preserving tasks such as log anomaly detection. While word-wise FHE schemes can perform additions and multiplications, complex functions such as Sigmoid need to be approximated. Probabilistic polynomial approximations using a Perceptron can achieve lower errors compared to deterministic approaches like Taylor and Chebyshev.
  • 203
  • 23 Oct 2023
Topic Review
Machine Learning in Cloud Computing
Cloud Computing is one of the emerging fields in the modern-day world. Due to the increased volume of job requests, job schedulers have received updates one at a time. The evolution of machine learning in the context of cloud schedules has had a significant impact on cost reduction in terms of energy consumption and makespan. 
  • 128
  • 23 Oct 2023
Topic Review
Mobile Government Services Adoption in the Egyptian Context
Customers are increasingly using mobile devices to locate merchants, conduct product research, make purchases, and manage their accounts. Mobile value-added services (VAS) is a term for services that are not included in standard phone plans and that must be purchased or downloaded separately by the end user. 
  • 179
  • 23 Oct 2023
Topic Review
Forensic Operations for Recognizing SQLite Content (FORC)
Mobile forensics is crucial in reconstructing various everyday activities accomplished through mobile applications during an investigation. Manual analysis can be tedious, time-consuming, and error-prone. Forensic Operations for Recognizing SQLite Content (FORC) is an automated tool specifically designed for Android to extract Simple Query Language Table Database Lightweight (SQLite) evidence.
  • 249
  • 23 Oct 2023
Topic Review
Deep Learning Methods for Retinal Disease Diagnosis
The advancement of digital medical imaging has brought about a significant change in ophthalmology as it has introduced effective technologies that help in the detection of such diseases. By improving early detection through image analysis and identifying minuscule anomalies, Artificial Intelligence (AI) has considerably coped with retinal diseases. Different Machine Learning (ML) and Convolutional Neural Networks (CNNs) are efficient at analyzing images and are particularly incredible at recognizing complex patterns in medical images.
  • 209
  • 21 Oct 2023
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