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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. 
  • 2.3K
  • 30 Nov 2023
Topic Review
Deep Learning towards Digital Additive Manufacturing
Machine learning is a type of deep learning. First in the machine learning (ML) process is the manual extraction of relevant image characteristics. These characteristics are also used to classify the image according to its particular characteristics. Researchers focused primarily on digital additive manufacturing, one of the most significant emerging topics in Industry 4.0.
  • 2.3K
  • 19 Dec 2022
Topic Review
Human-Computer Interaction System of Talking-Head Generation
Virtual human is widely employed in various industries, including personal assistance, intelligent customer service, and online education, thanks to the rapid development of artificial intelligence. An anthropomorphic digital human can quickly contact people and enhance user experience in human–computer interaction. 
  • 2.3K
  • 12 Jan 2023
Topic Review
Theoretical Background of Explainable Artificial Intelligence
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved and are now being employed in almost every application domain to develop automated or semi-automated systems. To facilitate greater human acceptability of these systems, explainable artificial intelligence (XAI) has experienced significant growth over the last couple of years with the development of highly accurate models but with a paucity of explainability and interpretability. XAI methods are mostly developed for safety-critical domains worldwide, deep learning and ensemble models are being exploited more than other types of AI/ML models, visual explanations are more acceptable to end-users and robust evaluation metrics are being developed to assess the quality of explanations.
  • 2.2K
  • 16 Mar 2022
Topic Review
5G Flying Ad Hoc Networks
Flying ad hoc network (FANET) is an application of 5G access network, which consists of unmanned aerial vehicles or flying nodes with scarce resources and high mobility rates. It is one of the new applications supported by 5G. 5G incorporates new technologies, including massive multiple-input and multiple-output (MIMO), device-to-device (D2D) communication, coordinated multi-point (CoMP), and beamforming, providing new features, such as exploring and exploiting mmWave and underutilized spectrum. 
  • 2.2K
  • 15 Apr 2022
Topic Review
Expert System for Earthquake Prediction
Earthquake is one of the most hazardous natural calamity. Many algorithms have been proposed for earthquake prediction using expert systems (ES). We aim to identify and compare methods, models, frameworks, and tools used to forecast earthquakes using different parameters. The analysis shows that most of the proposed models have attempted long term predictions about time, intensity, and location of future earthquakes. An investigation on different variants of rule-based, fuzzy, and machine learning based expert systems for earthquake prediction has been presented. Moreover, the discussion covers regional and global seismic data sets used, tools employed, to predict earth quake for different geographical regions. Bibliometric and meta-information based analysis has been performed by classifying the articles according to research type, empirical type, approach, target area, and system specific parameters.
  • 2.2K
  • 03 Feb 2021
Topic Review
Class Imbalance Problem in Credit Risk Prediction
Credit, as defined by financial institutions such as banks and lending companies, represents a vital loan certificate issued to individuals or businesses. This certification mechanism plays a pivotal role in ensuring the smooth functioning of the financial sector, contingent upon comprehensive evaluations of creditworthiness.
  • 2.2K
  • 18 Mar 2024
Topic Review
Deep Learning for Plant Disease Detection for Smart-Hydroponics
Recent advances in computing allows researchers to propose the automation of hydroponic systems to boost efficiency and reduce manpower demands, hence increasing agricultural produce and profit. A completely automated hydroponic system should be equipped with tools capable of detecting plant diseases in real-time. Deep-learning-based plant disease detection models leverage computer vision capability and come up with a model that can diagnose plant diseases by scanning plant leaves. The system is capable of diagnosing a given sample by simply taking the leaf image as input and returning the class of the disease that is affecting the plant on screen to ascertain whether the plant is healthy or not, alongside the name of the diseases that are affecting the plant.
  • 2.2K
  • 15 Jun 2022
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.
  • 2.2K
  • 10 Jan 2024
Topic Review
Homomorphic Encryption for Privacy-Preserving Biometrics
The advancement of biometric technology has facilitated wide applications of biometrics in law enforcement, border control, healthcare and financial identification and verification. Given the peculiarity of biometric features (e.g., unchangeability, permanence and uniqueness), the security of biometric data is a key area of research. Security and privacy are vital to enacting integrity, reliability and availability in biometric-related applications. Homomorphic encryption (HE) is concerned with data manipulation in the cryptographic domain, thus addressing the security and privacy issues faced by biometrics.
  • 2.2K
  • 16 Jun 2023
Topic Review
Determination of the Live Weight of Farm Animals
In cattle breeding, regularly taking the animals to the scale and recording their weight is important for both the performance of the enterprise and the health of the animals. This process, which must be carried out in businesses, is a difficult task. Due to the drawbacks of direct measurement approaches, a variety of indirect measurement approaches have been proposed.
  • 2.2K
  • 26 Jul 2023
Topic Review
AI-Driven Sentiment Analysis of Amazon Reviews Using BERT
Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. The pre-trained Bidirectional Encoder Representation from Transformers (BERT) model and the Text-to-Text Transfer Transformer (T5) are deployed to predict customer emotions. These models were trained on synthetically generated and manually labeled datasets to detect the specific features from review data, then sentiment analysis was performed to classify the data into positive, negative, and neutral reviews concerning their aspects. 
  • 2.2K
  • 17 Feb 2024
Topic Review Peer Reviewed
The Metaverse Territorial Brand: A Contemporary Concept
The “Metaverse Territorial Brand” integrates core and interconnected elements into a virtual, interactional, experiential, and immersive space known as the metaverse. This type of brand encompasses the connection with immersive territories that may or may not be digital twins of real territories. It also encompasses two interconnected physical scales: the territorial and the regional, involved in another type of emerging territorial scale, known as the metaversal scale. Therefore, the “Metaverse Territorial Brand” is a digital-immersive extension of the territorial brand of physical territories, encompassing specific geographical and cultural aspects, but directed to the metaverse environment. This brand is a symbolic digital construction, but also a multifaceted one that incorporates discursive and visual elements, articulated by the social actors of the immersive territory, aiming to create a specific and distinct identity for a space in the metaverse. When talking about social actors in the metaverse (users), we highlight that this set of actors may or may not be the same as the physical territory. It is also important to highlight that both the territorial brand directed to physical territories and the “Metaverse Territorial Brand” are formed from the power relations of a given set of social actors. Therefore, without the strategic intention of a plurality of social actors that stimulate these relationships, there is no type of territorial brand involved.
  • 2.2K
  • 29 Sep 2024
Topic Review
Deep Learning in Fashion and Apparel Retail Industry
Compared to other industries, fashion apparel retail faces many challenges in predicting future demand for its products with a high degree of precision. Fashion products’ short life cycle, insufficient historical information, highly uncertain market demand, and periodic seasonal trends necessitate the use of models that can contribute to the efficient forecasting of products’ sales and demand. Many researchers have tried to address this problem using conventional forecasting models that predict future demands using historical sales information. Machine learning and deep learning models such as the support vector machine, neural network, and recurrent neural network are among many forecast models that have gained popularity among forecast researchers and practitioners given their ability to overcome the drawbacks of traditional linear forecast models.
  • 2.2K
  • 01 Jul 2022
Topic Review
Aquaculture System Using Cloud-Based Autonomous Drones
Aquaculture System Using Cloud-Based Autonomous Drones incorporated artificial intelligence (AI) services using computer vision and combined various deep learning recognition models to achieve scalability and added functionality, in order to perform aquaculture surveillance tasks. The recognition model is embedded in the aquaculture cloud, to analyze images and videos captured by the autonomous drone. The recognition models detect people, cages, and ship vessels at the aquaculture site. The inclusion of AI functions for face recognition, fish counting, fish length estimation and fish feeding intensity provides intelligent decision making. For the fish feeding intensity assessment, the large amount of data in the aquaculture cloud can be an input for analysis using the AI feeding system to optimize farmer production and income. The autonomous drone and aquaculture cloud services are cost-effective and an alternative to expensive surveillance systems and multiple fixed-camera installations. The aquaculture cloud enables the drone to execute its surveillance task more efficiently with an increased navigation time. The mobile drone navigation app is capable of sending surveillance alerts and reports to users. Our multifeatured surveillance system, with the integration of deep-learning models, yielded high-accuracy results. 
  • 2.2K
  • 03 Nov 2021
Topic Review
Proxy Modeling Highlighting Applications for Reservoir Engineering
Numerical models can be used for many purposes in oil and gas engineering, such as production optimization and forecasting, uncertainty analysis, history matching, and risk assessment. However, subsurface problems are complex and non-linear, and making reliable decisions in reservoir management requires substantial computational effort. Proxy models have gained much attention in recent years. They are advanced non-linear interpolation tables that can approximate complex models and alleviate computational effort. Proxy models are constructed by running high-fidelity models to gather the necessary data to create the proxy model. Once constructed, they can be a great choice for different tasks such as uncertainty analysis, optimization, forecasting, etc. The application of proxy modeling in oil and gas has had an increasing trend in recent years, and there is no consensus rule on the correct choice of proxy model. As a result, it is crucial to better understand the advantages and disadvantages of various proxy models.
  • 2.2K
  • 05 Sep 2022
Topic Review
Food Image Dataset and Segmentation Model
The development of vision-based dietary assessment (VBDA) systems. These systems generally consist of three main stages: food image analysis, portion estimation, and nutrient derivation. The effectiveness of the initial step is highly dependent on the use of accurate segmentation and image recognition models and the availability of high-quality training datasets. Food image segmentation still faces various challenges, and most existing research focuses mainly on Asian and Western food images. 
  • 2.2K
  • 09 Jan 2024
Topic Review
Deep Learning for Classification of Skin Cancer
One of the major health concerns for human society is skin cancer. When the pigments producing skin color turn carcinogenic, this disease gets contracted. A skin cancer diagnosis is a challenging process for dermatologists as many skin cancer pigments may appear similar in appearance. Hence, early detection of lesions (which form the base of skin cancer) is definitely critical and useful to completely cure the patients suffering from skin cancer. Significant progress has been made in developing automated tools for the diagnosis of skin cancer to assist dermatologists. The worldwide acceptance of artificial intelligence-supported tools has permitted usage of the enormous collection of images of lesions and benevolent sores approved by histopathology.
  • 2.1K
  • 13 Dec 2021
Topic Review
Machine Learning Based Restaurant Sales Forecasting
A machine learning (ML) model is ideally trained using an optimal number of features and will capture fine details in the prediction task, such as holidays, without underperforming when the forecast window increases from one day to one week.
  • 2.1K
  • 10 Feb 2022
Topic Review
Machine Learning-Based Network Anomaly Detection
Artificial intelligence (AI) techniques have been used to describe the characteristics of information, as they help in the process of data mining (DM) to analyze data and reveal rules and patterns. In DM, anomaly detection is an important area that helps discover hidden behavior within the data that is most vulnerable to attack. It also helps detect network intrusion. Algorithms such as hybrid K-mean array and sequential minimal optimization (SMO) rating can be used to improve the accuracy of the anomaly detection rate. 
  • 2.1K
  • 19 Aug 2022
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