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Topic Review
Machine Learning and Artificial Intelligence
Machine learning (ML) is a type of artificial intelligence (AI) consisting of algorithmic approaches that enable machines to solve problems deprived of explicit computer programming. 
  • 1.1K
  • 28 Apr 2023
Topic Review
Literature
This is a list of encyclopedias as well as encyclopedic and biographical dictionaries published on the subject of literature in any language.
  • 1.3K
  • 28 Apr 2023
Topic Review
Effectiveness of Driving Simulators for Drivers’ Training
Although driving simulators could be commonly assumed as very useful technological resources for both novel and experienced drivers’ instruction under risk control settings, the evidence addressing their actual effectiveness seems substantially limited. Therefore, researchers aimed to analyze the existing original literature on driving simulators as a tool for driver training/instruction, considering study features, their quality, and the established degree of effectiveness of simulators for these purposes. Among a considerably reduced set of original research studies assessing the effectiveness of driving simulators for training purposes, most sources assessing the issue provided reasonably good insights into their value for improving human-based road safety under risk control settings. On the other hand, there are common limitations which stand out, such as the use of very limited research samples, infrequent follow-up of the training outcomes, and reduced information about the limitations targeted during the simulator-based training processes. Despite the key shortcomings highlighted here, studies have commonly provided empirical support on the training value of simulators, as well as endorsed the need for further evaluations of their effectiveness.
  • 396
  • 28 Apr 2023
Topic Review
Machine Learning-Based Forecasting of Renewable Energy
With the increasing penetration of renewable energy sources (RES) into the electricity grid, accurate forecasting of their generation becomes crucial for efficient grid operation and energy management. Traditional forecasting methods have limitations, and thus machine learning (ML) and deep learning (DL) algorithms have gained popularity due to their ability to learn complex relationships from data and provide accurate predictions.
  • 942
  • 27 Apr 2023
Topic Review
Knowledge Management in Agriculture
Achieving global food security requires better use of natural, genetic, and importantly, human resources—knowledge. Technology must be created, and existing and new technology and knowledge deployed, and adopted by farmers and others engaged in agriculture. This requires collaboration amongst many professional communities world-wide including farmers, agribusinesses, policymakers, and multi-disciplinary scientific groups. Each community having its own knowledge-associated terminology, techniques, and types of data, collectively forms a barrier to collaboration. Knowledge management (KM) approaches are being implemented to capture knowledge from all communities and make it interoperable and accessible as a “group memory” to create a multi-professional, multidisciplinary knowledge economy.
  • 1.1K
  • 25 Apr 2023
Topic Review
Generative Adversarial Network in Amodal Completion
The generative adversarial network (GAN) is a structured probabilistic model that consists of two networks, a generator that captures the data distributions and a discriminator that decides whether the produced data come from the actual data distribution or from the generator. The two networks train in a two-player minimax game fashion until the generator can generate samples that are similar to the true samples, and the discriminator can no longer distinguish between the real and the fake samples. Although current computer vision systems are closer to the human intelligence when it comes to comprehending the visible world than previously, their performance is hindered when objects are partially occluded. Since we live in a dynamic and complex environment, we encounter more occluded objects than fully visible ones. Therefore, instilling the capability of amodal perception into those vision systems is crucial. However, overcoming occlusion is difficult and comes with its own challenges. GAN, on the other hand, is renowned for its generative power in producing data from a random noise distribution that approaches the samples that come from real data distributions.
  • 632
  • 24 Apr 2023
Topic Review
Vision-Based Human Action Recognition Field
Artificial intelligence’s rapid advancement has enabled various applications, including intelligent video surveillance systems, assisted living, and human–computer interaction. These applications often require one core task: video-based human action recognition.
  • 334
  • 23 Apr 2023
Topic Review
Plus-Minus Sign
The plus-minus sign (±) is a mathematical symbol with multiple meanings. The sign is normally pronounced "plus or minus". In mathematics, it generally indicates a choice of exactly two possible values, one of which is the negation of the other. In experimental sciences, the sign commonly indicates the confidence interval or error in a measurement, often the standard deviation or standard error. The sign may also represent an inclusive range of values that a reading might have. In engineering the sign indicates the tolerance, which is the range of values that are considered to be acceptable, safe, or which comply with some standard, or with a contract. In botany it is used in morphological descriptions to notate "more or less". In chemistry the sign is used to indicate a racemic mixture. In chess, the sign indicates a clear advantage for the white player; the complementary sign ∓ indicates the same advantage for the black player.
  • 63.7K
  • 23 Apr 2023
Topic Review
Artificial Neural Networks for Navigation Systems
Several machine learning (ML) methodologies are gaining popularity as artificial intelligence (AI) becomes increasingly prevalent. An artificial neural network (ANN) may be used as a “black-box” modeling strategy without the need for a detailed system physical model. It is more reasonable to solely use the input and output data to explain the system’s actions. ANNs have been extensively researched, as artificial intelligence has progressed to enhance navigation performance. In some circumstances, the Global Navigation Satellite System (GNSS) can offer consistent and dependable navigational options. A key advancement in contemporary navigation is the fusion of the GNSS and inertial navigation system (INS). Numerous strategies have been put out to increase the accuracy for jamming, GNSS-prohibited environments, the integration of GNSS/INS or other technologies by means of a Kalman filter as well as to solve the signal blockage issue in metropolitan areas. A neural-network-based fusion approach is suggested to address GNSS outages. 
  • 830
  • 21 Apr 2023
Topic Review
Machine Learning-Based Approaches to IoT Localization
The widespread use of the Internet and the exponential growth in small hardware diversity enable the development of Internet of things (IoT)-based localization systems. Because of their high prediction accuracy, machine learning methods are being used to solve localization problems.
  • 320
  • 20 Apr 2023
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