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Topic Review
Pothole Detection
Many datasets used to train artificial intelligence systems to recognize potholes, such as the challenging sequences for autonomous driving (CCSAD) and the Pacific Northwest road (PNW) datasets, do not produce satisfactory results. This is due to the fact that these datasets present complex but realistic scenarios of pothole detection tasks than popularly used datasets that achieve better results but do not effectively represents realistic pothole detection task. In an attempt to improve the detection accuracy of the pothole object detection problems, researchers have proposed varieties of object detection methods enhanced with super-resolution (SR) techniques that are employed to generate an enhanced image from a low-resolution image before performing object detection.
  • 1.1K
  • 24 Jun 2022
Topic Review
A Patch-Based CNN Built on the VGG-16 Architecture
Facial recognition is a prevalent method for biometric authentication that is utilized in a variety of software applications. This technique is susceptible to spoofing attacks, in which an imposter gains access to a system by presenting the image of a legitimate user to the sensor, hence increasing the risks to social security. Consequently, facial liveness detection has become an essential step in the authentication process prior to granting access to users. A patch-based convolutional neural network (CNN) with a deep component for facial liveness detection for security enhancement was developed, which was based on the VGG-16 architecture.
  • 1.1K
  • 13 Sep 2022
Topic Review
Discrimination, Bias, Fairness, and Trustworthy AI
It has been identified that there exists a set of specialized variables, such as security, privacy, responsibility, etc., that are used to operationalize the principles in the Principled AI International Framework.  Bias, discrimination, and fairness are mainly approached with an operational interest by the Principled AI International Framework.
  • 1.1K
  • 01 Jul 2022
Topic Review
Image Segmentation Techniques
Image segmentation, which has become a research hotspot in the field of image processing and computer vision, refers to the process of dividing an image into meaningful and non-overlapping regions, and it is an essential step in natural scene understanding. 
  • 1.1K
  • 06 May 2023
Topic Review
Monitoring of Humans in Bed
Indeed, humans typically spend a significant portion of their daily lives in bed. This time becomes even longer in cases where the human is unwell. This is particularly the case for sick or older people, who spend even more time in bed. Their physical activity or inactivity patterns provide useful signatures that reflect the “state” of the person under observation. In the frame of activity monitoring endeavors, behavioral situations that are abnormal (these situations are more/extremely rare within the observation time window) are the ones that are of the highest interest when compared to behavioral situations that are rather normal (these ones occupy most of the observation time window).
  • 1.1K
  • 24 Aug 2022
Topic Review
Industrial Control Systems Technologies
Industrial Control Systems (ICS), which include Supervisory Control and Data Acquisition (SCADA) systems, Distributed Control Systems (DCS), and Programmable Logic Controllers (PLC), play a crucial role in managing and regulating industrial processes. However, ensuring the security of these systems is of utmost importance due to the potentially severe consequences of cyber attacks. 
  • 1.1K
  • 21 Nov 2023
Topic Review
Machine Learning and Fuzzy Logic in Electronics
Machine learning is a part of artificial intelligence science and works in close collaboration with data science. The main aim is the collected big data to be processed and studied in such a way to give meaningful knowledge when problems have to be solved or decisions have to be made. Fuzzy logic is another scientific field that is used for modeling, description and evaluation of objects and systems with different levels of complexity, which are characterized with uncertainty, fuzziness and vagueness of their parameters and properties. The application of machine learning and fuzzy logic in electronics is studied to outline the current research topics, scientific achievements and directions for future exploration.
  • 1.1K
  • 07 Dec 2021
Topic Review
Embedded Machine Learning
Embedded machine learning (EML) can be applied in the areas of accurate computer vision schemes, reliable speech recognition, innovative healthcare, robotics, and more. However, there exists a critical drawback in the efficient implementation of ML algorithms targeting embedded applications. Machine learning algorithms are generally computationally and memory intensive, making them unsuitable for resource-constrained environments such as embedded and mobile devices. In order to efficiently implement these compute and memory-intensive algorithms within the embedded and mobile computing space, innovative optimization techniques are required at the algorithm and hardware levels. 
  • 1.1K
  • 01 Nov 2021
Topic Review
Multimodal Segmentation Techniques in Autonomous Driving
Semantic Segmentation has become one of the key steps toward scene understanding, especially in autonomous driving scenarios. In the standard formulation, Semantic Segmentation uses only data from color cameras, which suffer significantly in dim lighting or adverse weather conditions. A solution to this problem is the use of multiple heterogeneous sensors (e.g., depth and thermal cameras or LiDARs) as the input to machine learning approaches tackling this task, allowing to cover for the shortcomings of color cameras and to extract a more resilient representation of the scene.
  • 1.1K
  • 15 Aug 2022
Topic Review
Machine Learning Methods in Weather and Climate Applications
With the rapid development of artificial intelligence, machine learning is gradually becoming popular for predictions in all walks of life. In meteorology, it is gradually competing with traditional climate predictions dominated by physical models. 
  • 1.1K
  • 15 Dec 2023
Topic Review
Technologies for Improving Storage Efficiency in Blockchain-Based IIoT
The Internet of Things (IoT) and blockchain have contributed to massive advancements in the fields to which they have been applied. The benefits of the blockchain, which include enhanced security, transparency, and greater traceability, make it a promising technology for integration with IIoT, which has long had issues with security. However, there are several issues that limit the integration of blockchain into Industrial Internet of Things (IIoT) systems. One of these issues is the huge storage requirement of the blockchain. There are several solutions to address these concerns. These solutions, which include summarization-based, compression-based, and storage scheme optimization methods, are necessary to enable the further development of blockchain–IIoT integration. However, these solutions have shortcomings that reduce their effectiveness. Compression-based schemes produce compressed blocks or data that accumulate over time and may not ensure enough storage savings on peers. This can be alleviated by designing compression techniques that provide an efficient representation of data for IIoT systems to yield better compression ratios. Summarization-based schemes reduce redundancy in block data by using the net change in transferring entities between parties and, thus, are better suited for financial systems than for IIoT systems. 
  • 1.1K
  • 30 Oct 2022
Topic Review
Fuel Consumption and CO2 of Light-Duty Vehicles
Due to the alarming rate of climate change, fuel consumption and emission estimates are critical in determining the effects of materials and stringent emission control strategies. In this research, an analytical and predictive study has been conducted using the Government of Canada dataset, containing 4973 light-duty vehicles observed from 2017 to 2021, delivering a comparative view of different brands and vehicle models by their fuel consumption and carbon dioxide emissions. Based on the findings of the statistical data analysis, this study makes evidence-based recommendations to both vehicle users and producers to reduce their environmental impacts. Additionally, Convolutional Neural Networks (CNN) and various regression models have been built to estimate fuel consumption and carbon dioxide emissions for future vehicle designs. This study reveals that the Univariate Polynomial Regression model is the best model for predictions from one vehicle feature input, with up to 98.6% accuracy. Multiple Linear Regression and Multivariate Polynomial Regression are good models for predictions from multiple vehicle feature inputs, with approximately 75% accuracy. Convolutional Neural Network is also a promising method for prediction because of its stable and high accuracy of around 70%. The results contribute to the quantifying process of energy cost and air pollution caused by transportation, followed by proposing relevant recommendations for both vehicle users and producers. Future research should aim towards developing higher performance models and larger datasets for building APIs and applications.
  • 1.1K
  • 20 Jan 2022
Topic Review
Deep Reinforcement Learning Approaches for Smart Manufacturing
AI and, in particular, the Deep Reinforcement Learning (DRL) algorithms, which are a perfect response to the unpredictability and volatility of modern demand, are studied in detail. Through the introduction of RL concepts and the development of those with ANNs towards DRL, the potential and variety of these kinds of algorithms are highlighted. Moreover, because these algorithms are data based, their modification to meet the requirements of industry operations is also included. Digital twins are a technology that is increasingly important in I.40 and I.5.0, which seems to be crucial to the development of smart manufacturing. 
  • 1.1K
  • 13 Jan 2023
Topic Review
Hashtag Recommendation
Hashtag recommendation suggests hashtags to users while they write microblogs in social media platforms. Although researchers have investigated various methods and factors that affect the performance of hashtag recommendations in Twitter and Sina Weibo, a systematic review of these methods is lacking.
  • 1.1K
  • 25 May 2021
Topic Review
Palmprint Recognition
Palmprint recognition constitutes a pivotal biometric technology deployed in the identification and verification of individuals, relying on the distinctive patterns inherent in their palmprints. This method, known for its reliability and security, finds extensive applications in diverse fields, including access control, security systems, and forensic investigations. Palmprint image acquisition involves capturing high-quality palmprint images using various devices like cameras, scanners, or smartphones. These images are then subjected to preprocessing techniques, encompassing noise reduction, normalization, and enhancement, to ensure consistent submission despite any restrictions on the availability of materials and/or refined input data. Following preprocessing, relevant features are extracted, like minutiae points specific to an individual’s palm, ridges, and lines. These features are crucial for accurate identification and are obtained through advanced image processing methods.
  • 1.1K
  • 10 Jan 2024
Topic Review
Artificial Intelligence in Agriculture: Benefits, Challenges, and Trends
The world’s population has reached 8 billion and is projected to reach 9.7 billion by 2050, increasing the demand for food production. Artificial intelligence (AI) technologies that optimize resources and increase productivity are vital in an environment that has tensions in the supply chain and increasingly frequent weather events. 
  • 1.1K
  • 05 Jul 2023
Topic Review
Federated Learning and Blockchain
The Internet of Things (IoT) compromises multiple devices connected via a network to perform numerous activities. The large amounts of raw user data handled by IoT operations have driven researchers and developers to provide guards against any malicious threats. Blockchain is a technology that can give connected nodes means of security, transparency, and distribution. IoT devices could guarantee data centralization and availability with shared ledger technology. Federated learning (FL) is a new type of decentralized machine learning (DML) where clients collaborate to train a model and share it privately with an aggregator node.
  • 1.1K
  • 30 Aug 2023
Topic Review
Sarcasm and Irony Detection in Social Media
Sarcasm and irony represent intricate linguistic forms in social media communication, demanding nuanced comprehension of context and tone. 
  • 1.1K
  • 30 Nov 2023
Topic Review
Radiomics of Liver Metastases
Multidisciplinary management of patients with liver metastases (LM) requires a precision medicine approach, based on adequate profiling of tumor biology and robust biomarkers. Radiomics, defined as the high-throughput identification, analysis, and translational applications of radiological textural features, could fulfill this need. The present review aims to elucidate the contribution of radiomic analyses to the management of patients with LM. We performed a systematic review of the literature through the most relevant databases and web sources. English language original articles published before June 2020 and concerning radiomics of LM extracted from CT, MRI, or PET-CT were considered. Thirty-two papers were identified. Baseline higher entropy and lower homogeneity of LM were associated with better survival and higher chemotherapy response rates. A decrease in entropy and an increase in homogeneity after chemotherapy correlated with radiological tumor response. Entropy and homogeneity were also highly predictive of tumor regression grade. In comparison with RECIST criteria, radiomic features provided an earlier prediction of response to chemotherapy. Lastly, texture analyses could differentiate LM from other liver tumors. The commonest limitations of studies were small sample size, retrospective design, lack of validation datasets, and unavailability of univocal cut-off values of radiomic features. In conclusion, radiomics can potentially contribute to the precision medicine approach to patients with LM, but interdisciplinarity, standardization, and adequate software tools are needed to translate the anticipated potentialities into clinical practice.
  • 1.0K
  • 06 Nov 2020
Topic Review
Business Recommender Systems
Besides the typical applications of recommender systems in B2C scenarios such as movie or shopping platforms, there is a rising interest in transforming the human-driven advice provided, e.g., in consultancy via the use of recommender systems. There are two main classes of recommender systems: information-filtering-based and knowledge-based systems. The former category selects items from a large collection of items based on user preferences and is further classified as collaborative-filtering recommenders and content-based filtering recommenders. The knowledge-based recommenders make recommendations by applying constraints or similarities based on domain or contextual knowledge. Common applications are in B2C scenarios such as e-commerce, tourism, news, movie, music, etc.
  • 1.0K
  • 10 Jun 2022
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