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Topic Review
Hierarchical Clustering Algorithms
In the field of data mining, clustering has shown to be an important technique. Hierarchical clustering algorithms are a type of clustering algorithm where data items will be divided into sections in a hierarchical form. To create a dendrogram that shows the formulated cluster’s hierarchical structure, in a top-down or bottom-up way clusters are created iteratively. 
  • 1.3K
  • 15 May 2023
Topic Review
Deepfake Identification and Traceability
Researchers and companies have released multiple datasets of face deepfakes labeled to indicate different methods of forgery. Naming these labels is often arbitrary and inconsistent. However, researchers must use multiple datasets in practical applications to conduct traceability research. The researchers utilize the K-means clustering method to identify datasets with similar feature values and analyze the feature values using the Calinski Harabasz Index method. Datasets with the same or similar labels in different deepfake datasets exhibit different forgery features. The KCE system can solve this problem, which combines multiple deepfake datasets according to feature similarity. In the model trained based on KCE combined data, the Calinski Harabasz scored 42.3% higher than the combined data by the same forgery name. It shows that this method improves the generalization ability of the model.
  • 1.3K
  • 08 Jun 2023
Topic Review
Explainable AI (XAI) Explanation Techniques
Interest in artificial intelligence (AI) has been increasing rapidly over the past decade and has expanded to essentially all domains. Along with it grew the need to understand the predictions and suggestions provided by machine learning. Explanation techniques have been researched intensively in the context of explainable AI (XAI), with the goal of boosting confidence, trust, user satisfaction, and transparency.
  • 1.3K
  • 19 Jun 2023
Topic Review
Facial Information for Healthcare Applications
The document is not limited to global face analysis but it also concentrates on methods related to local cues (e.g. the eyes). A research taxonomy is introduced by dividing the face in its main features: eyes, mouth, muscles, skin, and shape. For each facial feature, the computer vision-based tasks aiming at analyzing it and the related healthcare goals that could be pursued are detailed.
  • 1.3K
  • 28 Oct 2020
Topic Review
COVID-19 Fake News in Brazilian Portuguese Language
Public health interventions to counter the COVID-19 pandemic have accelerated and increased digital adoption and use of the Internet for sourcing health information. Unfortunately, there is evidence to suggest that it has also accelerated and increased the spread of false information relating to COVID-19. The consequences of misinformation, disinformation and misinterpretation of health information can interfere with attempts to curb the virus, delay or result in failure to seek or continue legitimate medical treatment and adherence to vaccination, as well as interfere with sound public health policy and attempts to disseminate public health messages. While there is a significant body of literature, datasets and tools to support countermeasures against the spread of false information online in resource-rich languages such as English and Chinese, there are few such resources to support Portuguese, and Brazilian Portuguese specifically.
  • 1.3K
  • 29 Apr 2022
Topic Review
ProMatch: Semi-Supervised Learning with Prototype Consistency
Semi-supervised learning (SSL) methods have made significant advancements by combining consistency-regularization and pseudo-labeling in a joint learning paradigm. The core concept of these methods is to identify consistency targets (pseudo-labels) by selecting predicted distributions with high confidence from weakly augmented unlabeled samples. 
  • 1.3K
  • 04 Sep 2023
Topic Review
GIS and Reinforcement Learning for Aquaculture Disease Transmission
Aquaculture, a critical domain in sustainable food production, is increasingly relying on Geographic Information Systems (GIS) for disease transmission analysis. GIS, an advanced digital mapping and analytical tool, not only helps visualize the geographical spread of diseases but also discerns patterns and offers predictive insights. By integrating a variety of datasets, from environmental to biological, GIS enables comprehensive analysis of disease risk zones, facilitating preemptive measures and efficient resource allocation.
  • 1.3K
  • 23 Nov 2023
Topic Review
Artificial Neural Networks and Energy Forecasting
Load prediction with higher accuracy and less computing power has become an important problem in the smart grids domain in general and especially in demand-side management (DSM), as it can serve to minimize global warming and better integrate renewable energies. Indeed, artificial neural networks (ANN) are the most used methods in forecasting electrical load. They are widely employed in this field for their numerous advantages. In fact, the complexity of this task is considerable due to several factors/parameters, such as weather and holidays (linear and non-linear relationships), which is a well-suited problem for ANNs and their capacity to deal with non-linear relationships.
  • 1.3K
  • 21 Jun 2022
Topic Review
Artificial Intelligence (AI)-Empowered Echocardiography Interpretation
Echocardiography (Echo), a widely available, noninvasive, and portable bedside imaging tool, is the most frequently used imaging modality in assessing cardiac anatomy and function in clinical practice. Artificial-intelligence-empowered echo (AI-Echo) can potentially reduce inter-interpreter variability and indeterminate assessment and improve the detection of unique conditions as well as the management of various cardiac disorders.
  • 1.3K
  • 28 Apr 2021
Topic Review
Lhia as A Chatbot for Breastfeeding Education
Human milk is the most important way to feed and protect newborns as it has the components to ensure human health. Human Milk Banks (HMBs) form a network that offers essential services to ensure that newborns and mothers can take advantage of the benefits of human milk.
  • 1.3K
  • 16 Jun 2023
Topic Review
Methods for Melanoma and Nonmelanoma Skin Cancers Classification
Skin cancer is considered a dangerous type of cancer with a high global mortality rate. Manual skin cancer diagnosis is a challenging and time-consuming method due to the complexity of the disease. In the field of transfer learning and federated learning, there are several new algorithms and techniques for classifying melanoma and nonmelanoma skin cancer.
  • 1.3K
  • 19 Oct 2023
Topic Review
Synthetic Image Data in Computer Vision
Many computer vision applications cannot rely on general image data provided in the available public datasets to train models, instead requiring labelled image data that is not readily available in the public domain on a large scale. At the same time, acquiring such data from the real world can be difficult, costly to obtain, and manual labour intensive to label in large quantities. Because of this, synthetic image data has been pushed to the forefront as a potentially faster and cheaper alternative to collecting and annotating real data.
  • 1.3K
  • 15 Dec 2022
Topic Review
Intrusion Detection System in IoT Wi-Fi Networks
The Internet of Things (IoT) is a network of billions of interconnected devices embedded with sensors, software, and communication technologies. Wi-Fi is one of the main wireless communication technologies essential for establishing connections and facilitating communication in IoT environments. However, IoT networks are facing major security challenges due to various vulnerabilities, including de-authentication and disassociation DoS attacks that exploit IoT Wi-Fi network vulnerabilities. Traditional intrusion detection systems (IDSs) improved their cyberattack detection capabilities by adapting machine learning approaches, especially deep learning (DL). However, DL-based IDSs still need improvements in their accuracy, efficiency, and scalability to properly address the security challenges including de-authentication and disassociation DoS attacks tailored to suit IoT environments. The main purpose of this research was to overcome these limitations by designing a transfer learning (TL) and convolutional neural network (CNN)-based IDS for deauthentication and disassociation DoS attack detection with better overall accuracy compared to various current solutions. 
  • 1.3K
  • 15 Oct 2023
Topic Review
Sign Language Recognition
Recognition of hand motion capture is an interesting topic. Hand motion can represent many gestures. In particular, sign language plays an important role in the daily lives of hearing-impaired people. Sign language recognition is essential in hearing-impaired people’s communication. Wearable data gloves and computer vision are partially complementary solutions. However, sign language recognition using a general monocular camera suffers from occlusion and recognition accuracy issues.
  • 1.3K
  • 08 Dec 2023
Topic Review
Knee Injury Detection Using Deep Learning
Knee injuries account for the largest percentage of sport-related, severe injuries (i.e., injuries that cause more than 21 days of missed sport participation). The improved treatment of knee injuries critically relies on having an accurate and cost-effective detection. Deep-learning-based approaches have monopolized knee injury detection in MRI studies.
  • 1.3K
  • 20 May 2022
Topic Review
AI Advancements
Artificial intelligence (AI) has seen remarkable advancements, stretching the limits of what is possible and opening up new frontiers. Beginning with the fundamentals of AI, including traditional machine learning and the transition to data-driven approaches, the narrative progresses through core AI techniques such as reinforcement learning, generative adversarial networks, transfer learning, and neuroevolution.
  • 1.3K
  • 28 Dec 2023
Topic Review
Deep Learning for Motor Imagery Brain–Computer Interface
The field of brain–computer interface (BCI) enables us to establish a pathway between the human brain and computers, with applications in the medical and nonmedical field. Brain computer interfaces can have a significant impact on the way humans interact with machines. In recent years, the surge in computational power has enabled deep learning algorithms to act as a robust avenue for leveraging BCIs. 
  • 1.3K
  • 17 Oct 2023
Topic Review
Universal Intelligence for Sustainability
Artificial intelligence (AI), as a product of biological intelligence, is a technological tool based on data and the information-processing power of discrete machines that carry out a series of interdependent operations to generate and store discrete data and information, using discrete, finite, and closed algorithms. In turn, the concept of sustainability is increasingly considered an almost essential component of discourses designed to support and justify decision-making at all levels of human activities.  The strong and functional couplings among ecological, economic, social, and technological processes explain the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, and the power of information, and the COVID-19 syndemic. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy, and information, and a given time horizon. Given the high stakes; the need for effective, efficient, diverse solutions; their local and global, and present and future effects; and their unforeseen short-, medium-, and long-term impacts; achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents (SUIAs). The proposed philosophical and technological SUIAs will be heuristic devices for harnessing the strong functional coupling between human, artificial, and nonhuman biological intelligence in a non-zero-sum game to achieve sustainability.
  • 1.3K
  • 21 Jun 2022
Topic Review
Opium Poppy Detection in Unmanned Aerial Vehicle Imagery
Opium poppy is a medicinal plant, and its cultivation is illegal without legal approval in China. Unmanned aerial vehicle (UAV) is an effective tool for monitoring illegal poppy cultivation. Unmanned aerial vehicle (UAV) is more flexible and mobile than remote sensing satellite, and their high-resolution images can help to detect poppies in areas that are hard to see. 
  • 1.3K
  • 18 Feb 2024
Topic Review
Decision Support Systems in Forestry and Tree-Planting Practices
Using deep neural networks (DNNs), a decision support system (DSS) can be trained to learn from a large dataset of tree data, including information about tree species, climate, soil conditions, and other factors that influence tree growth and survival. This is because the use of neural networks was proposed three decades ago to solve forest management problems by integrating forest knowledge with artificial intelligence (AI). AI greatly benefits sustainability and the preservation of ecosystem values, as increasing disruptions in a changing world can only be managed beyond human intelligence. Furthermore, despite the various DSSs and AI systems used, the appointment of appropriate project managers is crucial to the execution and subsequent success of a project.
  • 1.3K
  • 04 Mar 2024
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