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Topic Review
Decentralized Multi-Robot Collision Avoidance
When deploying a multi-robot system, it is ensured that the hardware parts do not collide with each other or the surroundings, especially in symmetric environments. Two types of methods are used for collision avoidance: centralized and decentralized. The decentralized approach has mainly been used in recent times, as it is computationally less expensive.
  • 1.3K
  • 19 Apr 2022
Topic Review
Machine Learning for Crop Diseases and Pests
Rapid population growth has resulted in an increased demand for agricultural goods. Pests and diseases are major obstacles to achieving this productivity outcome. Therefore, it is very important to develop efficient methods for the automatic detection, identification, and prediction of pests and diseases in agricultural crops. To perform such automation, Machine Learning (ML) techniques can be used to derive knowledge and relationships from the data that is being worked on. 
  • 1.3K
  • 16 Sep 2022
Topic Review
Camera-LiDAR-Based 3D Object Detection Methods
Three-dimensional (3D) object detection is a topic that has gained interest within the scientific community dedicated to vehicle automation. Based on LiDAR and stereo cameras, and considering only deep learning-based approaches, 3D object detection methods are classified according to the type of input data: camera-based, LiDAR-based, and fusion-based 3D object detection.
  • 1.3K
  • 15 Mar 2024
Topic Review
Handwritten Chinese Text Recognition
Offline handwritten Chinese recognition is an important research area of pattern recognition, including offline handwritten Chinese character recognition (offline HCCR) and offline handwritten Chinese text recognition (offline HCTR), which are closely related to daily life. HCTR is more complex and relatively less accurate due to the unconstrained nature of text lines and the adhesion between characters. It can be further divided into line-level HCTR and page-level HCTR depending on whether the recognition object is a cropped image of a text line or an entire page.
  • 1.3K
  • 24 Mar 2023
Topic Review
Intelligent Energy Management Systems for Electric Vehicle Transportation
Electric Vehicles (EVs) have been gaining interest as a result of their ability to reduce vehicle emissions. Developing an intelligent system to manage EVs charging demands is one of the fundamental aspects of this technology to better adapt for all-purpose transportation utilization. It is necessary for EVs to be connected to the Smart Grid (SG) to communicate with charging stations and other energy resources in order to control charging schedules, while Artificial Intelligent (AI) techniques can be beneficial for improving the system, they can also raise security and privacy threats. Privacy preservation methodologies have been introduced to ensure data security. Federated Learning (FL) and blockchain technology are two emerging strategies to address information protection concerns. 
  • 1.3K
  • 22 Nov 2022
Topic Review
AI-Based Conversational Large Language Models
The demand for psychological counselling has grown significantly in recent years, particularly with the global outbreak of COVID-19, which heightened the need for timely and professional mental health support. Online psychological counselling emerged as the predominant mode of providing services in response to this demand. The Psy-LLM framework, an AI-based assistive tool leveraging large language models (LLMs) for question answering in psychological consultation settings to ease the demand on mental health professions.
  • 1.3K
  • 02 Jan 2024
Topic Review
Artificial Intelligence Surgery
Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intelligence (AI) has grown exponentially with the development of machine learning (ML), deep learning (DL), computer vision (CV) and natural language processing (NLP). This entry will highlight the most recent issues regarding how AI will get us to more autonomous actions in surgery by discussing the different degrees of surgical autonomy, recent advances with reinforcement learning and the ethical roadblocks that lie ahead.
  • 1.3K
  • 25 Aug 2021
Topic Review
Wavelet Threshold Denoising Algorithm
The denoising performance is affected by several factors, including wavelet basis function, decomposition level, thresholding method, and the threshold selection criteria. Traditional threshold selection rules rely on statistical and empirical variables, which influence their performance in noise reduction under various conditions. 
  • 1.3K
  • 06 Jul 2022
Topic Review
Brain Tumor Detection Using Federated Learning
Brain tumor segmentation in medical imaging is a critical task for diagnosis and treatment while preserving patient data privacy and security. Traditional centralized approaches often encounter obstacles in data sharing due to privacy regulations and security concerns, hindering the development of advanced AI-based medical imaging applications.
  • 1.3K
  • 08 Nov 2023
Topic Review
Techniques Related to Chinese Speech Emotion Recognition
The use of Artificial Intelligence for emotion recognition has attracted much attention. The industrial applicability of emotion recognition is quite comprehensive and has good development potential. 
  • 1.3K
  • 12 Jul 2022
Topic Review
Machine Learning Techniques for Customer Churn Prediction
The application of various machine learning techniques for predicting customer churn in the telecommunications sector is explored. Researchers utilized a publicly accessible dataset and implemented several models, including Artificial Neural Networks, Decision Trees, Support Vector Machines, Random Forests, Logistic Regression, and gradient boosting techniques (XGBoost, LightGBM, and CatBoost). To mitigate the challenges posed by imbalanced datasets, researchers adopted different data sampling strategies, namely SMOTE, SMOTE combined with Tomek Links, and SMOTE combined with Edited Nearest Neighbors. Moreover, hyperparameter tuning was employed to enhance model performance. Resarchers' evaluation employed standard metrics, such as Precision, Recall, F1-score, and the Receiver Operating Characteristic Area Under Curve (ROC AUC). In terms of the F1-score metric, CatBoost demonstrates superior performance compared to other machine learning models, achieving an outstanding 93% following the application of Optuna hyperparameter optimization. In the context of the ROC AUC metric, both XGBoost and CatBoost exhibit exceptional performance, recording remarkable scores of 91%. This achievement for XGBoost is attained after implementing a combination of SMOTE with Tomek Links, while CatBoost reaches this level of performance after the application of Optuna hyperparameter optimization.
  • 1.3K
  • 12 Dec 2023
Topic Review
Automatic Identification of Addresses
Address matching continues to play a central role at various levels, through geocoding and data integration from different sources, with a view to promote activities such as urban planning, location-based services, and the construction of databases like those used in census operations. Closely associated to address matching is the task of address parsing or address segmentation, which consists of decomposing an address into its different components, such as a street name or a postal code. However, these tasks continue to face several challenges, such as non-standard or incomplete address records or addresses written in more complex languages.
  • 1.3K
  • 10 Jan 2022
Topic Review
Fine-Grained Change Detection
Fine-grained change detection in sensor data is very challenging for artificial intelligence though it is critically important in practice. It is the process of identifying differences in the state of an object or phenomenon where the differences are class-specific and are difficult to generalise. As a result, many recent technologies that leverage big data and deep learning struggle with this task.
  • 1.3K
  • 12 Jul 2021
Topic Review
Lightweight Convolutional Neural Network
Biometrics has become an important research issue, and the use of deep learning neural networks has made it possible to develop more reliable and efficient recognition systems. Palms have been identified as one of the most promising candidates among various biometrics due to their unique features and easy accessibility.
  • 1.3K
  • 31 Jul 2023
Topic Review
Digital Twins
Digital Twins, which are virtual representations of physical systems mirroring their behavior, enable real-time monitoring, analysis, and optimization. Understanding and identifying the temporal dependencies included in the multivariate time series data that characterize the behavior of the system are crucial for improving the effectiveness of Digital Twins. Long Short-Term Memory (LSTM) networks have been used to represent complex temporal dependencies and identify long-term links in the Industrial Internet of Things (IIoT).
  • 1.3K
  • 03 Nov 2023
Topic Review
Visual Simultaneous Localization and Mapping
Visual Simultaneous Localization and Mapping (VSLAM) methods refer to the SLAM approaches that employ cameras for pose estimation and map reconstruction and are preferred over Light Detection And Ranging (LiDAR)-based methods due to their lighter weight, lower acquisition costs, and richer environment representation.
  • 1.3K
  • 30 Dec 2022
Topic Review
Grammar Correction for Multiple Errors in Chinese
Grammar Error Correction (GEC) is a key task in the field of Natural Language Processing (NLP). Its purpose is to automatically detect and correct grammatical errors in sentences, and it holds immense research value. The mainstream methods for grammar correction primarily rely on sequence tagging and text generation, which are two end-to-end approaches. These methods demonstrate exemplary performance in domains with low error density, but often fail to provide satisfactory results in high error density situations where multiple errors exist in a single sentence. As a result, these methods tend to over-correct correct words, leading to a high false alarm rate.
  • 1.3K
  • 24 Aug 2023
Topic Review
Augmented Reality Mobile App to Learn Writing
Augmented reality (AR) has been widely used in education, particularly for child education. This entry presents the design and implementation of a novel mobile app, Learn2Write, using machine learning techniques and augmented reality to teach alphabet writing.
  • 1.3K
  • 10 Jan 2022
Topic Review
Monocular Depth Estimation with Deep Learning
Significant advancements in robotics engineering and autonomous vehicles have improved the requirement for precise depth measurements. Depth estimation (DE) is a traditional task in computer vision that can be appropriately predicted by applying numerous procedures.  This is vital in disparate applications such as augmented reality and target tracking. Conventional monocular DE (MDE) procedures are based on depth cues for depth prediction. Various deep learning techniques have demonstrated their potential applications in managing and supporting the traditional ill-posed problem.
  • 1.3K
  • 12 Aug 2022
Topic Review
Bilinear Filtering
Bilinear filtering is a texture filtering method used to smooth textures when displayed larger or smaller than they actually are. Most of the time, when drawing a textured shape on the screen, the texture is not displayed exactly as it is stored, without any distortion. Because of this, most pixels will end up needing to use a point on the texture that is "between" texels – assuming the texels are points (as opposed to, say, squares) – in the middle (or on the upper left corner, or anywhere else; it does not matter, as long as it is consistent) of their respective "cells". Bilinear filtering uses these points to perform bilinear interpolation between the four texels nearest to the point that the pixel represents (in the middle or upper left of the pixel, usually).
  • 1.3K
  • 02 Nov 2022
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