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Topic Review
Indoor Hydroponic Greenhouses
Indoor hydroponic greenhouses are becoming increasingly popular for sustainable food production. On the other hand, precise control of the climate conditions inside these greenhouses is crucial for the success of the crops. Time series deep learning models are adequate for climate predictions in indoor hydroponic greenhouses, but a comparative analysis of these models at different time intervals is needed.
  • 788
  • 26 Jun 2023
Topic Review
Algorithms for Facial Expression Recognition in the Wild
Facial expression recognition (FER) in the wild has attracted much attention due to its wide range of applications. Approaches use deep learning models trained on relatively large images, which significantly reduces their accuracy when they have to infer low-resolution images.
  • 788
  • 22 Sep 2023
Topic Review
Relevant Approaches of Zero Trust Network Model
Zero Trust Architecture research is now in its early stages, with a primary focus on the framework itself, access control, algorithms of trust evaluation, and identity authentication. These are the primary study domains within the Zero Trust field.
  • 788
  • 29 Feb 2024
Topic Review
LiDAR Point Clouds Semantic Segmentation in Autonomous Driving
Although semantic segmentation of 2D images is crucial to attaining scene understanding, there are still some limitations to visual sensors, such as the inefficiency of acquiring information under insufficient light, lack of depth information and limited field of view. In contrast, LiDAR can obtain accurate depth information with higher density and wider viewing field regardless of lighting conditions, which makes it a more reliable source of information for environmental perception.
  • 787
  • 24 Jan 2024
Topic Review
Finger Vein Verification
Traditional technologies of personal identity authentication (e.g., tokens, cards, PINs) have been gradually replaced by some more-advanced biometrics technologies, including faces, retinas, irises, fingerprints, veins, etc. Among these, the finger vein (FV) trait, due to its unique advantages of high security, the living requirement, being non-contact, and not easily being injured or counterfeited, has drawn extensive attention after it appeared. Different from some visual imaging traits such as faces and fingerprints, the main veins in the fingers tend to be longitudinally distributed in the subcutaneous regions.
  • 786
  • 28 Jul 2023
Topic Review
Taxonomy of Machine Learning Methods for Urban Applications
Machine Learning (ML) as an intersection of informatics and statistics is a promising challenge for more evidence-based decisions to fill in the gap of existing technological tools and instruments for spatiotemporal requirements. As ML transcended the conventional techniques of modeling, a huge potential of big data management to address complex city problems is presented at the crossroads of modern urban planning challenges to make up their dynamics. Generally speaking, the ML methods are categorized based on the type of ‘learning’.
  • 784
  • 10 Jan 2023
Topic Review
Federated Learning and Blockchain Applications in Vehicular Networks
The Internet of Things (IoT) revitalizes the world with tremendous capabilities and potential to be utilized in vehicular networks. The Smart Transport Infrastructure (STI) era depends mainly on the IoT. Advanced machine learning (ML) techniques are being used to strengthen the STI smartness further. However, some decisions are very challenging due to the vast number of STI components and big data generated from STIs. Computation cost, communication overheads, and privacy issues are significant concerns for wide-scale ML adoption within STI. These issues can be addressed using Federated Learning (FL) and blockchain. FL can be used to address the issues of privacy preservation and handling big data generated in STI management and control. Blockchain is a distributed ledger that can store data while providing trust and integrity assurance. Blockchain can be a solution to data integrity and can add more security to the STI.  While transmitting data, valuable information can be disclosed through the model parameters by reverse engineering. The disclosure of valuable data motivated researchers and developers to adopt known security and privacy defense methods, e.g., functional encryption and differential privacy, to FL.
  • 782
  • 17 Jun 2022
Topic Review
Autonomous Vehicles and Distributed Resources on Logistic Systems
The autonomous vehicle (AV) is one of the emerging technologies of the new age that has the potential to restructure transportation infrastructure. AVs are able to sense their surroundings and move around with control and self-sufficiency. AVs can contribute towards reducing traffic congestion on the roads, improving the quality of life, and achieving the highest levels of traffic safety. Thus, this type of vehicle can be integrated into the logistics industry. Due to the presence of several AVs, selecting a standard and efficient AV for logistics planning is a great challenge. The selection of an AV depends on many conflicting and essential criteria. 
  • 781
  • 31 Aug 2023
Topic Review
Diffusion-Based Method for Pavement Crack Detection
Pavement crack detection is of significant importance in ensuring road safety and smooth traffic flow. However, pavement cracks come in various shapes and forms which exhibit spatial continuity, and algorithms need to adapt to different types of cracks while preserving their continuity. Some studies have already applied the feature learning capability of generative models to crack detection. 
  • 781
  • 01 Apr 2024
Topic Review
Conversational Chatbots
A conversational chatbot or dialogue system is a computer program designed to simulate conversation with human users, especially over the Internet. These chatbots can be integrated into messaging apps, mobile apps, or websites, and are designed to engage in natural language conversations with users.
  • 780
  • 03 Mar 2023
Topic Review
Mass Appraisal Models of Real Estate Tax Value
Artificial neural network (ANN)-based analysis can reveal differences in tax leakage loss rates in different geographical regions of countries. Experts can adjust a region’s valuation data based on property tax leakage loss rates. Appraisers can contribute to solving the problem by highlighting areas with high tax leakage loss rates and communicating their findings to valuation stakeholders, local administrators, and policymakers. This can lead to more fair and efficient tax policies that benefit the real estate sector and the economy.
  • 780
  • 23 Oct 2023
Topic Review
New Semantic Segmentation Method for Remote Sensing Images
Semantic segmentation is an important task for the interpretation of remote sensing images. Remote sensing images are large in size, contain substantial spatial semantic information, and generally exhibit strong symmetry, resulting in images exhibiting large intraclass variance and small interclass variance, thus leading to class imbalance and poor small-object segmentation.
  • 779
  • 08 Jun 2023
Topic Review
Explainable Artificial Intelligence in Healthcare
Artificial Intelligence (AI) describes computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. AI can be applied in many different areas, such as econometrics, biometry, e-commerce, and the automotive industry. AI has found its way into healthcare as well, helping doctors make better decisions, localizing tumors in magnetic resonance images, reading and analyzing reports written by radiologists and pathologists, and much more. However, AI has one big risk: it can be perceived as a “black box”, limiting trust in its reliability, which is a very big issue in an area in which a decision can mean life or death. As a result, the term Explainable Artificial Intelligence (XAI) has been gaining momentum. XAI tries to ensure that AI algorithms (and the resulting decisions) can be understood by humans.
  • 778
  • 23 Aug 2023
Topic Review
Automatic Genre Identification for Massive Text Collections
Automatic genre identification is a text classification task, as a method of providing insights into the content of large text collections. It evaluates various machine learning models for their generalization capabilities, including pre-Transformer approaches, BERT-like encoder models and instruction-tuned GPT large language models. As a result, it introduces the first publicly-available benchmark for this task. What is more, a high-performing genre classifier that can be applied to numerous languages is introduced.
  • 778
  • 30 Oct 2023
Topic Review
Assessment of Parent–Child Interaction Quality from Dyadic Dialogue
The quality of parent–child interaction is critical for child cognitive development. The Dyadic Parent–Child Interaction Coding System (DPICS) is commonly used to assess parent and child behaviors. However, manual annotation of DPICS codes by parent–child interaction therapists is a time-consuming task. To assist therapists in the coding task, researchers have begun to explore the use of artificial intelligence in natural language processing to classify DPICS codes automatically.
  • 777
  • 20 Nov 2023
Topic Review
AI-Supported Programming Tasks
AI-assisted programming or development is defined as the utilization of machine learning models trained on the vast amount of available source code. Its purpose is to support various aspects of programming and, more broadly, software engineering implementation tasks. 
  • 777
  • 19 Feb 2024
Topic Review
Sign Language Recognition Techniques
Historically, individuals with hearing impairments have faced neglect, lacking the necessary tools to facilitate effective communication. Building a sign language recognition system using deep learning technology plays a vital role in interpreting sign language to ordinary individuals and the reverse. This system would ease the process of communication between deaf and normal people.
  • 776
  • 10 Oct 2023
Topic Review
Raft (Computer Science)
Raft is a consensus algorithm designed as an alternative to the Paxos family of algorithms. It was meant to be more understandable than Paxos by means of separation of logic, but it is also formally proven safe and offers some additional features. Raft offers a generic way to distribute a state machine across a cluster of computing systems, ensuring that each node in the cluster agrees upon the same series of state transitions. It has a number of open-source reference implementations, with full-specification implementations in Go, C++, Java, and Scala. It is named after Reliable, Replicated, Redundant, And Fault-Tolerant. Raft is not a Byzantine fault tolerant algorithm: the nodes trust the elected leader.
  • 774
  • 31 Oct 2022
Topic Review
Text Generation Models and Imbalanced Sentiment Analysis
The significance of sentiment analysis has extended across a wide range of fields, finding extensive use in various applications. As digital communication continues to expand, the ability of sentiment analysis to interpret complex human emotions and opinions becomes increasingly important, proving invaluable in fields ranging from social sciences to customer service and beyond. In this era of increasing digitization, leveraging the power of data through sentiment analysis offers unique insights, making significant contributions to sectors such as those previously summarized in various studies, namely, healthcare, social policy, e-commerce, and digital humanities.
  • 774
  • 18 Sep 2023
Topic Review
Near-Infrared Band Simulation Using Conditional Generative Adversarial Network
Multispectral sensors are important instruments for Earth observation. In remote sensing applications, the near-infrared (NIR) band, together with the visible spectrum (RGB), provide abundant information about ground objects.
  • 773
  • 31 Jul 2023
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