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Topic Review
Salp Swarm Algorithm
The Salp Swarm Algorithm (SSA) is a bio-inspired metaheuristic optimization technique that mimics the collective behavior of Salp chains hunting for food in the ocean. While it demonstrates competitive performance on benchmark problems, the SSA faces challenges with slow convergence and getting trapped in local optima like many population-based algorithms. 
  • 1.1K
  • 26 Jan 2024
Topic Review
Smart Agriculture
Smart agriculture, or precision agriculture, is a crucial way to achieve greater yields by utilizing the natural deposits in a diverse environment. The yield of a crop may vary from year to year depending on the variations in climate, soil parameters and fertilizers used. Automation in the agricultural industry moderates the usage of resources and can increase the quality of food in the post-pandemic world. Agricultural robots have been developed for crop seeding, monitoring, weed control, pest management and harvesting. Physical counting of fruitlets, flowers or fruits at various phases of growth is labour intensive as well as an expensive procedure for crop yield estimation. Remote sensing technologies offer accuracy and reliability in crop yield prediction and estimation. The automation in image analysis with computer vision and deep learning models provides precise field and yield maps. In this review, it has been observed that the application of deep learning techniques has provided a better accuracy for smart farming. The crops taken for the study are fruits such as grapes, apples, citrus, tomatoes and vegetables such as sugarcane, corn, soybean, cucumber, maize, wheat. The research works which are carried out in this research paper are available as products for applications such as robot harvesting, weed detection and pest infestation. The methods which made use of conventional deep learning techniques have provided an average accuracy of 92.51%.
  • 1.1K
  • 28 Apr 2021
Topic Review
Blockchain and Energy Internet
Emergence of the Energy Internet (EI) demands restructuring of traditional electricity grids to integrate heterogeneous energy sources, distribution network management with grid intelligence and big data management. This paradigm shift is considered to be a breakthrough in the energy industry towards facilitating autonomous and decentralized grid operations while maximizing the utilization of Distributed Generation (DG). Blockchain has been identified as a disruptive technology enabler for the realization of EI to facilitate reliable, self-operated energy delivery. 
  • 1.1K
  • 12 Aug 2021
Topic Review
Challenges in Agricultural Image Datasets and Filter Algorithms
Smart farming is facilitated by remote sensing because it allows for the inexpensive monitoring of crops, crop classification, stress detection yield forecasting using lightweight sensors over a wide area in a relatively short amount of time. Deep learning (DL)-based computer vision is one of the important aspects of the automatic detection and monitoring of plant stress. Challenges for DL algorithms in the agricultural dataset include size variation in objects, image resolution, background clutter, precise annotation with the expert, high object density or the demand for different spectral images.
  • 1.1K
  • 07 Mar 2024
Topic Review
Universal Functions Originator
Universal Functions Originator, or just UFO, is a new multi-purpose machine learning (ML) computing system that explains everything as pure mathematical equations. These expressions could be simple or highly complicated linear/nonlinear equations. Although the purpose of this technique is similar to that of classical symbolic regression (SR) algorithms, UFO works differently and it has its own mechanism, search space, and building strategy. For example, in UFO, each equation term (of intercepts, weights, exponents, arithmetic operators, and analytic functions) has its own search space and cannot be mixed with others. Also, UFO can be executed by any optimization algorithm, while SR algorithms require some special tree-based optimization algorithms; like genetic programming (GP).
  • 1.1K
  • 24 Oct 2022
Topic Review
Using Colored Petri Net for Accounting System
Many learners who are not familiar with the accounting terms find blended learning very complex to understand with respect to the computerized accounting system, the journal entries process, and tracing the accounting transaction flows of accounting system. A simulation-based model is a viable option to help instructors and learners make understanding the accounting system components and monitoring the accounting transactions easier. This entry briefly introduce a colored Petri net (CPN)-based model.
  • 1.1K
  • 28 Mar 2022
Topic Review
Energy Consumption Patterns in Urban Buildings
Energy has been one of the most important topics of political and social discussion in recent decades. A significant proportion of the country’s revenues is derived from energy resources, making it one of the most important and strategic macro policy and sustainable development areas. Energy demand modeling is one of the essential strategies for better managing the energy sector and developing appropriate policies to increase productivity. With the increasing global demand for energy, it is necessary to develop intelligent forecasting methods and algorithms. Different economic and non-economic indicators can be used to estimate the energy demand, including linear and non-linear statistical methods, mathematics, and simulation models.
  • 1.1K
  • 28 Apr 2022
Topic Review
Artificial Intelligence in Alzheimer’s Disease
Alzheimer’s disease (AD) represents most of the dementia cases and stands as the most common neurodegenerative disease. A shift from a curative to a preventive approach is imminent, and we are moving towards the application of personalized medicine, whereas we can shape the best clinical intervention for each patient at a given point. This new step in medicine requires the most recent tools and the analysis of huge amounts of data where the application of artificial intelligence (AI) plays a critical part in the depiction of disease-patient dynamics, critical to reach early/optimal diagnosis, monitoring and intervention. Predictive models and algorithms are the key elements in this innovative field. 
  • 1.1K
  • 02 Mar 2022
Topic Review
Deep Learning-Based Methods for Crop Disease Estimation
Deep learning methods such as U-Net, SegNet, YOLO, Faster R-CNN, VGG and ResNet have been used extensively for crop disease estimation using Unmanned Aerial Vehicle (UAV)  imagery. The basic building block of the deep learning architecture is basically the success of convolutional neural networks (CNN). The deep learning models implemented for crop disease estimation using UAV imagery can be categorized into classification-based, segmentation-based and detection-based approaches. Segmentation-based models attempt to classify each pixel in an image into different categories such as healthy vs. diseased pixels, whereas classification-based models look into overall images and classify the image into pre-defined disease classes.
  • 1.1K
  • 16 May 2023
Topic Review
Background of Machine/Deep Learning Approaches on Mental Health
Mental health can be seen as a person’s emotional, psychological, and social well-being. It can be harmed by various mental health conditions, which negatively influence a person’s intellectual capacity, emotions, and social relationships. Machine learning (ML) is a subfield of artificial intelligence (AI) that deals with three problems: classification, regression, and clustering. It utilizes data and algorithms to mimic how people learn while progressively improving accuracy in various tasks.
  • 1.1K
  • 08 Feb 2023
Topic Review
Train Multiplayer First-Person Shooter Game Agents
Artificial Intelligence bots are extensively used in multiplayer First-Person Shooter (FPS) games. By using Machine Learning techniques, we can improve their performance and bring them to human skill levels.
  • 1.1K
  • 18 Mar 2024
Topic Review
Computer-Assisted Tissue Image Analysis in Minimally Invasive Surgery
Computer-assisted tissue image analysis (CATIA) enables an optical biopsy of human tissue during minimally invasive surgery and endoscopy. Thus far, it has been implemented in gastrointestinal, endometrial, and dermatologic examinations that use computational analysis and image texture feature systems.
  • 1.1K
  • 21 Dec 2021
Topic Review
Analysing Hucul Horses by AI
       The neural classification system in form of a multi-layered artificial neural network suggested in this paper was implemented in the programming environment MATLAB. MATLAB is a useful tool focused mainly on scientific and technical calculations. It boasts of a wide spectrum of software solutions/libraries, the so-called Toolboxes that can be used, for example to create and optimize neural networks. It is fully compatible with other programming environments.  Matlab is a tool for rapid prototyping that enables a wide range of learning algorithms, the selection of optimal neural network architecture, the selection of the most efficient neuron activation functions as well as optimal learning parameters.          The design of the network is of key significance both for the learning process, and the quality of its operation in later stages. The set of input data, purpose, and results do have significant impact on the they configuration.  A key assumption is taking cognizance of factual links between the set of explanatory variables (input) and the output.        The artificial neural networks enable the capture of relationships and dependencies between the data in circumstances where the application of traditional analytical methods would not have yielded satisfactory solutions.         The use of ANN enables objective assessments of individual animals by taking into account only factors essential for determining horses’ performance and breeding values.         Preliminary results of the application of artificial neural networks in predicting the utility value of Hucul horses, relying on a specific set of features seem rather promising.        It offers potential possibilities of evaluation, relying on available information about the animals.
  • 1.1K
  • 13 Oct 2020
Topic Review
Automated Stuttering Classification
Speech disfluency, particularly stuttering, can have a significant impact on effective communication. Stuttering is a speech disorder characterized by repetitions, prolongations, and blocks in the flow of speech, which can result in communication difficulties, social isolation, and low self-esteem. Stuttering can also lead to negative reactions from listeners, such as impatience or frustration, which can further exacerbate communication difficulties.
  • 1.1K
  • 07 Oct 2023
Topic Review
Enhancing Collaborative Filtering-Based Recommender System Using Sentiment Analysis
Recommendation systems (RSs) are widely used in e-commerce to improve conversion rates by aligning product offerings with customer preferences and interests. While traditional RSs rely solely on numerical ratings to generate recommendations, these ratings alone may not be sufficient to offer personalized and accurate suggestions. To overcome this limitation, additional sources of information, such as reviews, can be utilized. However, analyzing and understanding the information contained within reviews, which are often unstructured data, is a challenging task. To address this issue, sentiment analysis (SA) has attracted considerable attention as a tool to better comprehend a user’s opinions, emotions, and attitudes.
  • 1.1K
  • 21 Aug 2023
Topic Review
Update on Cyber Health Psychology
In recent years, there has been more and more talk of cyber health psychology and the implication that new technologies can have in the diagnosis, treatment, and rehabilitation of psychopathological issues in the field of mental health, ranging from post-traumatic stress disorder (PTSD) to addiction to substances of abuse.
  • 1.1K
  • 25 Mar 2022
Topic Review
Deep Learning in COVID-19
Various deep-learning (DL) methods that utilize a combination of omics data and imaging data have been applied to the diagnosis, prognosis, and treatment options of clinical COVID-19 patients. Even with the emerging deep-learning methods, human intervention is still essential in the clinical diagnosis and treatment of COVID-19 patients.
  • 1.1K
  • 06 Apr 2023
Topic Review
Brain Tumor Segmentation
Segmentation of brain tumor images from magnetic resonance imaging (MRI) is a challenging topic in medical image analysis. The brain tumor can take many shapes, and MRI images vary considerably in intensity, making lesion detection difficult for radiologists. Image segmentation is the action of grouping pixels according to predefined criteria, in order to build regions or classes of pixels. There are several methods of image segmentation: methods based on contours, regions, classification, or hybrid. Segmentation and its automation remain today one of the major challenges in MRI, mainly in relation to brain tumor images, in order to help the practitioner in his daily practice, in the presence of a huge volume of images. 
  • 1.1K
  • 26 Sep 2022
Topic Review
Deep Learning Approach for Lung Cancer Diagnosis
Deep learning has emerged as a powerful tool for medical image analysis and diagnosis, demonstrating high performance on tasks such as cancer detection. As deep learning techniques continue to revolutionize the field of medical imaging, researchers have increasingly turned to large-scale databases to train and validate their algorithms. Many studies have been done to diagnose lung cancer using different datasets, both public and private. Each dataset has its own unique characteristics and challenges.
  • 1.1K
  • 18 Feb 2024
Topic Review
Forensic Methods for Image Inpainting
The rapid development of digital image inpainting technology is causing serious hidden danger to the security of multimedia information. Efforts have been devoted to developing forensic methods for image inpainting. They can be roughly divided into the following two categories: conventional inpainting forensics methods and deep learning-based inpainting forensics methods.
  • 1.1K
  • 26 Jun 2023
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