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Topic Review
Handwritten Character Recognition in Handwritten Character Recognition
Neural networks have made big strides in image classification. Convolutional neural networks (CNN) work successfully to run neural networks on direct images. Handwritten character recognition (HCR) is now a very powerful tool to detect traffic signals, translate language, and extract information from documents, etc. Although handwritten character recognition technology is in use in the industry, present accuracy is not outstanding, which compromises both performance and usability.
  • 2.1K
  • 13 May 2022
Topic Review
Artificial Intelligence Applications and Self-Learning 6G Networks
Artificial Intelligence (AI), federated and distributed learning, big data analytics, blockchain, and edge-cloud computing has urged the design of the upcoming 6G network generation, due to their stringent requirements in terms of the quality of services (QoS), availability, and dependability to satisfy a Service-Level-Agreement (SLA) for the end users. Industries and academia have started to design 6G networks and propose the use of AI in its protocols and operations. 
  • 2.0K
  • 02 Sep 2022
Topic Review
Autonomous Underwater Vehicles
Development of Autonomous Underwater Vehicles (AUV's) has permitted the automatization of many tasks originally achieved with manned vehicles in underwater environments. Teams of AUV's designed to work within a common mission are opening the possibilities for new and more complex applications. In underwater environments, communication, localization, and navigation of AUV's are considered challenges due to the impossibility of relying on radio communications and global positioning systems. For a long time, acoustic systems have been the main approach for solving these challenges. However, they present their own shortcomings, which are more relevant for AUV's teams. As a result, researchers have explored different alternatives. To summarize and analyze these alternatives, a review of the literature is presented in this paper. Finally, a summary of collaborative AUV's teams and missions is also included, with the aim of analyzing their applicability, advantages, and limitations.
  • 2.0K
  • 28 Oct 2020
Topic Review
Crop Yield Prediction Approaches
Crop yield prediction is becoming more important because of the growing concern about food security. Early crop yield prediction plays an important role in reducing famine by estimating the food availability for the growing world population. Deep learning has emerged as a potential tool for crop yield prediction, allowing the model to automatically extract features and learn from the datasets. Meanwhile, smart farming technology enables the farmers to achieve maximum crop yield by extracting essential parameters of crop growth.
  • 2.0K
  • 12 May 2022
Topic Review
Prediction of Customer Churn in Retail E-Commerce Business
Customer Relationship Management (CRM) is defined as a process in which the business manages its interactions with customers using data integration from various sources and data analysis.
  • 2.0K
  • 18 Jan 2022
Topic Review
Deep Learning Algorithms and Their Applications
Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as supervised, semi-supervised, or unsupervised learning strategies to learn automatically in deep architectures and has gained much popularity due to its superior ability to learn from huge amounts of data.
  • 1.9K
  • 17 Mar 2022
Topic Review
Detection of Image Steganography
As internet traffic grows daily, so does the need to protect it. Network security protects data from unauthorized access and ensures their confidentiality and integrity. Steganography is the practice and study of concealing communications by inserting them into seemingly unrelated data streams (cover media). Investigating and adapting machine learning models in digital image steganalysis is becoming more popular.
  • 1.9K
  • 28 Jun 2023
Topic Review
Moz (Marketing Software)
Moz is a software as a service (SaaS) company based in Seattle that sells inbound marketing and marketing analytics software subscriptions. It was founded by Rand Fishkin and Gillian Muessig in 2004 as a consulting firm and shifted to SEO software development in 2008. The company hosts a website that includes an online community of more than one million globally based digital marketers and marketing related tools. Moz offers SEO tools that includes keyword research, link building, site audits, and page optimization insights in order to help companies to have a better view of the position they have on search engines and how to improve their ranking. The company also developed the most commonly used algorithm to determine Domain Authority, which is a score between 1-100, that is often used by many SEO companies to estimate a website's overall viability with the search engines.
  • 1.9K
  • 18 Oct 2022
Topic Review
URL Normalization
URL normalization is the process by which URLs are modified and standardized in a consistent manner. The goal of the normalization process is to transform a URL into a normalized URL so it is possible to determine if two syntactically different URLs may be equivalent. Search engines employ URL normalization in order to assign importance to web pages[clarify] and to reduce indexing of duplicate pages. Web crawlers perform URL normalization in order to avoid crawling the same resource more than once. Web browsers may perform normalization to determine if a link has been visited or to determine if a page has been cached.
  • 1.9K
  • 18 Oct 2022
Topic Review
Artificial Intelligence Applied to Photovoltaic Systems
Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. Artificial intelligence (AI) is used to solve the most important problems found in photovoltaic (PV) systems, such as the tracking of the Max Power Point of the PV modules, the forecasting of the energy produced by the PV system, the estimation of the parameters of the equivalent model of PV modules or the detection of faults found in PV modules or cells. AI techniques perform better than classical approaches, even though they have some limitations such as the amount of data and the high computation times needed for performing the training.
  • 1.9K
  • 24 Oct 2022
Topic Review
3D Point Cloud Classification
Three-dimensional (3D) point cloud classification methods based on deep learning have good classification performance. The 3D point cloud is mainly collected by light detection and ranging (LiDAR) scanner, red, green, blue, and depth (RGB-D) camera, and other sensor equipment or obtained by model conversion using computer software.
  • 1.9K
  • 10 Jun 2022
Topic Review
Artificial Intelligence as a Disruptive Technology
The greatest technological changes in our lives are predicted to be brought about by Artificial Intelligence (AI). Together with the Internet of Things (IoT), blockchain, and several others, AI is considered to be the most disruptive technology, and has impacted numerous sectors, such as healthcare (medicine), business, agriculture, education, and urban development.
  • 1.8K
  • 07 Jul 2023
Topic Review
Avalanche (Consensus Protocol)
Avalanche is a protocol for solving consensus in a network of unreliable machines, where failures may be crash-fault or Byzantine. The protocol was anonymously introduced on IPFS on May 2018 and was formalized in more detail by Cornell University researchers in 2019. The protocol has four basic interrelated mechanisms that compose structural support of the consensus tool. These four mechanisms are Slush, Snowflake, Snowball, and Avalanche. By using uses randomized sampling and metastability to ascertain and persist transactions, It represents a new protocol family. Although the original paper focused on a single protocol, namely Avalanche, it implicitly introduced a broad spectrum of voting-based, or quorum-based consensus protocols, called the Snow family. While Avalanche is a single instantiation, the Snow family seems to be able to generalize all quorum-based voting protocols for replica control. Unlike prior quorum-based work, the Snow family enables arbitrarily parametrizable failure probability at the quorum intersection level. Standard quorum-based protocols define this failure probability to be precisely zero, but by introducing errors in the quorum intersection, a larger set of consensus protocol design is available.
  • 1.8K
  • 03 Nov 2022
Topic Review
AI and General movements (GMs)
       General movements (GMs) are spontaneous movements of infants up to five months post-term involving the whole body varying in sequence, speed, and amplitude. The assessment of GMs has shown its importance for identifying infants at risk for neuromotor deficits, especially for the detection of cerebral palsy. As the assessment is based on videos of the infant that are rated by trained professionals, the method is time-consuming and expensive. Therefore, approaches based on Artificial Intelligence have gained significantly increased attention in the last years.
  • 1.8K
  • 18 Feb 2021
Topic Review
Classifications of Routing Protocols in Ad hoc Networks
Wireless Mobile Ad-hoc Networks (WANETs-MANETs) are one of the most in-demand networks in our day and age, being widely used in military fields, disaster environments, autonomous robots, vehicular networks, rural and urban environments, and UAV applications. This is due to the remarkable features of versatility, robustness, and self-configuration with no infrastructure. Such networks' main objective is to deliver reliable data transmission directly to nodes such routers, access points, smartphones, and vehicles with dynamically adjusting the data routes in accordance with the network conditions and GPS information. However, mobility in ad hoc networks is yet the crucial issue due to the dynamic changes of the network topology; this makes data routing a substantial challenge. To this end, choosing or design the proper routing protocol plays important role in establishing robust, secure and efficient data communication for randomly distributed and unrestricted movement of nodes.
  • 1.8K
  • 10 Oct 2023
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. 
  • 1.8K
  • 15 Apr 2022
Topic Review
The Modulation Recognition Method Based on Deep Learning
Deep learning is a powerful artificial intelligence technology that can learn features from a large amount of data and fit nonlinear networks, so it is widely used in the fields of computer vision, natural language processing, and speech recognition, and has achieved tremendous success. Since mobile communication networks are able to generate large amounts of different types of data at a very fast pace, relevant researchers have applied deep learning to the field of communication, bringing opportunities for the development of communication technologies. For example, signal modulation identification in wireless communication can be done using deep learning techniques, and deep learning-based modulation identification methods have better robustness than traditional AMR methods and higher accuracy rates. There are many excellent neural networks in deep learning, such as convolutional neural network (CNN), recurrent neural network (RNN), etc. Among them, CNN is good at processing image data and RNN is good at processing sequence signals. CNN and RNN are widely used in AMR. The application of these neural networks to deep learning is discussed.
  • 1.8K
  • 08 Oct 2022
Topic Review
Noise Removal Filter for LiDAR Point Clouds
Light Detection and Ranging (LiDAR) is a critical sensor for autonomous vehicle systems, providing high-resolution distance measurements in real-time. However, adverse weather conditions such as snow, rain, fog, and sun glare can affect LiDAR performance, requiring data preprocessing.
  • 1.7K
  • 24 May 2023
Topic Review
Accelerometer-Based Human Fall Detection
Human falls are a global public health issue resulting in over 37.3 million severe injuries and 646,000 deaths yearly. Falls result in direct financial cost to health systems and indirectly to society productivity. Unsurprisingly, human fall detection and prevention is a major focus of health research. In this article, we consider deep learning for fall detection in an IoT and fog computing environment. We propose a Convolutional Neural Network composed of three convolutional layers, two maxpool, and three fully-connected layers as our deep learning model. We evaluate its performance using three open data sets and against extant research. Our approach for resolving dimensionality and modelling simplicity issues is outlined. Accuracy, precision, sensitivity, specificity, and the Matthews Correlation Coefficient are used to evaluate performance. The best results are achieved when using data augmentation during the training process. 
  • 1.7K
  • 20 Jan 2021
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.
  • 1.7K
  • 16 Mar 2022
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