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Topic Review
Applications of Deep Reinforcement Learning in Other Industries
Reinforcement Learning (RL) is an approach to simulate the human’s natural learning process, whose key is to let the agent learn by interacting with the stochastic environment. 
  • 1.4K
  • 29 Nov 2021
Topic Review
Applications of Brain–Computer Interfaces to Control and Automation
Brain–computer interfacing (BCI) is a real-time communication system that connects the brain and external devices. A BCI system can directly convert the information sent by the brain into commands that can drive external devices and can replace human limbs or phonation organs to achieve communication with the outside world and to control the external environment. In other words, a BCI system can replace the normal peripheral nerve and muscle tissue to achieve communication between a human and a computer or between a human and the external environment. BCIs have been validated in various noisy structured environments such as homes, hospitals, and expositions, resulting in the direct application of BCIs gaining popularity with regular consumers.
  • 1.4K
  • 12 Jun 2023
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.
  • 1.4K
  • 10 Jun 2022
Topic Review
Machine Learning for Precision Agriculture with UAV
Unmanned aerial vehicles (UAVs) are increasingly being integrated into the domain of precision agriculture, revolutionizing the agricultural landscape. Specifically, UAVs are being used in conjunction with machine learning techniques to solve a variety of complex agricultural problems. 
  • 1.4K
  • 19 Jun 2023
Topic Review
LiFi Network
Light Fidelity (LiFi), a new technology that uses light to transmit data as a high-speed wireless connection system from a wide spectrum of domains.
  • 1.4K
  • 01 Dec 2021
Topic Review
Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage
In the cultural heritage field, point clouds, as important raw data of geomatics, are not only three-dimensional (3D) spatial presentations of 3D objects but they also have the potential to gradually advance towards an intelligent data structure with scene understanding, autonomous cognition, and a decision-making ability. The approach of point cloud semantic segmentation as a preliminary stage can help to realize this advancement.
  • 1.4K
  • 09 Mar 2023
Topic Review
Machine Failure Prediction Using Survival Analysis
With the rapid growth of cloud computing and the creation of large-scale systems such as IoT environments, the failure of machines/devices and, by extension, the systems that rely on them is a major risk to their performance, usability, and the security systems that support them. The need to predict such anomalies in combination with the creation of fault-tolerant systems to manage them is a key factor for the development of safer and more stable systems. 
  • 1.4K
  • 19 Oct 2023
Topic Review
HAR in Smart Homes
Human Activity Recognition (HAR) consists in monitoring and analyzing the behavior of one or more persons in order to deduce their activity. In a smart home context, the HAR consists in monitoring daily activities of the residents, based on a network of IoT devices. Owing to this monitoring, a smart home can offer personalized home assistance services to improve quality of life, autonomy and health of their residents, especially for elderly and dependent people.
  • 1.4K
  • 19 Nov 2021
Topic Review
Transformers for Computer Vision
Vision transformers (ViTs) are designed for tasks related to vision, including image recognition. Originally, transformers were used to process natural language (NLP). As a special type of transformer, vision transformers (ViTs) can be used for various computer vision (CV) applications.
  • 1.4K
  • 09 May 2023
Topic Review
NNetEn Entropy
NNetEn is the first entropy measure that is based on artificial intelligence methods. The method modifies the structure of the LogNNet classification model so that the classification accuracy of the MNIST-10 digits dataset indicates the degree of complexity of a given time series. The calculation results of the proposed model are similar to those of existing methods, while the model structure is completely different and provides considerable advantages.
  • 1.4K
  • 19 Jun 2023
Topic Review Peer Reviewed
Tokenization in the Theory of Knowledge
Tokenization is a procedure for recovering the elements of interest in a sequence of data. This term is commonly used to describe an initial step in the processing of programming languages, and also for the preparation of input data in the case of artificial neural networks; however, it is a generalizable concept that applies to reducing a complex form to its basic elements, whether in the context of computer science or in natural processes. In this entry, the general concept of a token and its attributes are defined, along with its role in different contexts, such as deep learning methods. Included here are suggestions for further theoretical and empirical analysis of tokenization, particularly regarding its use in deep learning, as it is a rate-limiting step and a possible bottleneck when the results do not meet expectations.
  • 1.4K
  • 11 Apr 2023
Topic Review
Unmanned Aerial Vehicles and Federated Learning
Unmanned aerial vehicles (UAVs) have gained increasing attention in boosting the performance of conventional networks due to their small size, high efficiency, low cost, and autonomously nature. The amalgamation of UAVs with both distributed/collaborative Deep Learning (DL) algorithms, such as Federated Learning (FL), and Blockchain technology have ushered in a new paradigm of Secure Multi-Access Edge Computing (S-MEC). Indeed, FL enables UAV devices to leverage their sensed data to build local DL models. The latter are then sent to a central node, e.g., S-MEC node, for aggregation, in order to generate a global DL model. Therefore, FL enables UAV devices to collaborate during several FL rounds in generating a learning model, while avoiding to share their local data, and thus ensuring UAVs’ privacy.
  • 1.4K
  • 22 Jul 2022
Topic Review
Applying Machine Learning in Retail Demand Prediction
In the realm of retail supply chain management, accurate forecasting is paramount for informed decision making, as it directly impacts business operations and profitability. 
  • 1.4K
  • 19 Oct 2023
Topic Review
Traditional Computer-Vision Methods Implemented in Sports
Automatic analysis of video in sports is a possible solution to the demands of fans and professionals for various kinds of information. Analyzing videos in sports has provided a wide range of applications, which include player positions, extraction of the ball’s trajectory, content extraction, and indexing, summarization, detection of highlights, on-demand 3D reconstruction, animations, generation of virtual view, editorial content creation, virtual content insertion, visualization and enhancement of content, gameplay analysis and evaluations, identifying player’s actions, referee decisions and other fundamental elements required for the analysis of a game. Recent developments in video analysis of sports have a focus on the features of computer vision techniques, which are used to perform certain operations for which these are assigned, such as detailed complex analysis such as detection and classification of each player based on their team in every frame or by recognizing the jersey number to classify players based on their team will help to classify various events where the player is involved. In higher-level analysis, such as tracking the player or ball, many more such evaluations are to be considered for the evaluation of a player’s skills, detecting the team’s strategies, events and the formation of tactical positions such as midfield analysis in various sports such as soccer, basketball, and also various sports vision applications such as smart assistants, virtual umpires, assistance coaches. A higher-level semantic interpretation is an effective substitute, especially in situations when reduced human intervention and real-time analysis are desired for the exploitation of the delivered system outputs.
  • 1.4K
  • 19 May 2022
Topic Review
Privacy-Preserving and Explainable AI
The industrial environment has gone through the fourth revolution, also called “Industry 4.0”, where the main aspect is digitalization. Each device employed in an industrial process is connected to a network called the industrial Internet of things (IIOT). With IIOT manufacturers being capable of tracking every device, it has become easier to prevent or quickly solve failures. Specifically, the large amount of available data has allowed the use of artificial intelligence (AI) algorithms to improve industrial applications in many ways (e.g., failure detection, process optimization, and abnormality detection).
  • 1.4K
  • 01 Jul 2022
Topic Review
Use of Deep Learning for Video Classification
Deep learning models, specifically convolutional neural networks (CNNs), are well known for understanding images. An artificial neural network (ANN) is an algorithm based on interconnected nodes to recognize the relationships in a set of data. Algorithms based on ANNs have shown a great success in modeling both the lineßar and the non-linear relationships in the underlying data. Due to the huge success rate of these algorithms, they are extensively being used for different real-time applications.
  • 1.4K
  • 15 May 2023
Topic Review
Compensation of Pressure Sensor Drifts
Pressure sensor chips embodied in very tiny packages are deployed in a wide range of advanced applications. Examples of them range from industrial to altitude location services. They are also becoming increasingly pervasive in many other fields, ranging from industrial to military to consumer. However, these sensors, which are very cheap to manufacture in silicon, are strongly affected by thermal, mechanical and environmental stresses, which ultimately affect their measurement accuracy in the form of variations in gain, hysteresis, and nonlinear responses. To compensate induced drift in measurements, several neural networks were devised and be applied to stresses caused by two thermal cycles: 260 C for 10-40 seconds (JEDEC soldering procedure) and 100 C for two hours. These models were characterized in accuracy and deployability on tiny embedded devices and improved accuracy was observed.
  • 1.4K
  • 08 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. 
  • 1.4K
  • 30 Oct 2022
Topic Review
Fashion Recommendation System Using Deep Learning
Recommender systems are one of the great improvements in Internet technology and e-commerce, and the origins of modern recommender systems date back to the early 1990s when they were mainly applied experimentally to personal email and information filtering. Later, recommender systems went through numerous improvements to facilitate users’ navigation through fashion, videos, books, papers, and especially e-commerce.
  • 1.4K
  • 22 Aug 2023
Topic Review
Lightweight IoT Intrusion Detection Systems
Cyber security has become increasingly challenging due to the proliferation of the Internet of Things (IoT), where a massive number of tiny, smart devices push trillion bytes of data to the Internet and is expected to reach 73.1 ZB (zettabytes) by 2025. IoT devices have limited computational capabilities and thus researchers have shifted their focus onto designing lightweight intrusion-detection system (IDS) that can deliver the needed security requirements while operating on those thin devices.
  • 1.4K
  • 29 Aug 2023
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