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Topic Review
Wind–Solar Hybrid System Modeling
Wind–solar hybrid systems combine solar photovoltaic cells and wind turbines to produce power from both solar and wind energy.
  • 189
  • 31 May 2023
Topic Review
Web Search Results Exploration for Blind Users
In the contemporary digital landscape, web search functions as a pivotal conduit for information dissemination. Nevertheless, blind users (BUs) encounter substantial barriers in leveraging online services, attributable to intrinsic deficiencies in the information structure presented by online platforms. A critical analysis reveals that a considerable segment of BUs perceive online service access as either challenging or unfeasible, with only a fraction of search endeavors culminating successfully. 
  • 97
  • 21 Nov 2023
Topic Review
Wearable Sensors and Computer-Vision-Based Methods
Real-time sensing and modeling of the human body, especially the hands, is an important research endeavor for various applicative purposes such as in natural human computer interactions. Hand pose estimation is a big academic and technical challenge due to the complex structure and dexterous movement of human hands. Boosted by advancements from both hardware and artificial intelligence, various prototypes of data gloves and computer-vision-based methods have been proposed for accurate and rapid hand pose estimation in recent years. However, existing reviews either focused on data gloves or on vision methods or were even based on a particular type of camera, such as the depth camera. The purpose of this survey is to conduct a comprehensive and timely review of recent research advances in sensor-based hand pose estimation, including wearable and vision-based solutions. Hand kinematic models are firstly discussed. An in-depth review is conducted on data gloves and vision-based sensor systems with corresponding modeling methods. Particularly, this review also discusses deep-learning-based methods, which are very promising in hand pose estimation. Moreover, the advantages and drawbacks of the current hand gesture estimation methods, the applicative scope, and related challenges are also discussed.
  • 1.3K
  • 22 Feb 2021
Topic Review
Weakly Supervised Object Detection for Remote Sensing Images
To account for the lack of fine-grained annotations, such as object bounding boxes, several object detection methods have been developed that leverage only coarse-grain annotations (especially image-level labels indicating only the presence or absence of an object). This approach is called inexact Weak Supervision and introduces a new branch of Object Detection called Weakly Supervised Object Detection. Given an image, Remote Sensing Fully Supervised Object Detection (RSFSOD) aims to locate and classify objects based on Bounding Boxes annotations. Differently from RSFSOD, Remote Sensing Weakly Supervised Object Detection aims to precisely locate and classify object instances in Remote Sensing Images using only image-level labels or other types of coarse-grained labels (e.g., points or scribbles) as ground truth. 
  • 332
  • 24 Nov 2022
Topic Review
Weakly Supervised Crowd-Counting Models
Crowd-counting networks have become the mainstream method to deploy crowd-counting techniques on resource-constrained devices. Significant progress has been made in this field, with many outstanding lightweight models being proposed successively.  However, challenges like scare variation, global feature extraction, and fine-grained head annotation requirements still exist in relevant tasks, necessitating further improvement. In this research, the researchers propose a weakly-supervised hybrid lightweight crowd-counting network that integrates the initial layers of GhostNet as the backbone to efficiently extract local features and enrich intermediate features. The experimental results for accuracy and inference speed evaluation on some mainstream datasets validate the effective design principle of the model.
  • 49
  • 28 Feb 2024
Topic Review
Weakly Supervised and Unsupervised Methods in Plant Segmentation
Plant segmentation is a challenging computer vision task due to plant images complexity. We need to distinguish plant parts rather than the whole plant. The major complication of multi-part segmentation is the absence of well-annotated datasets. It is very time-consuming and expensive to annotate datasets manually on the object parts level.
  • 210
  • 04 Aug 2023
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. 
  • 335
  • 06 Jul 2022
Topic Review
Walking Recognition in Mobile Devices
Presently, smartphones are used more and more for purposes that have nothing to do with phone calls or simple data transfers. One example is the recognition of human activity, which is relevant information for many applications in the domains of medical diagnosis, elderly assistance, indoor localization, and navigation. The information captured by the inertial sensors of the phone (accelerometer, gyroscope, and magnetometer) can be analyzed to determine the activity performed by the person who is carrying the device, in particular in the activity of walking. Nevertheless, the development of a standalone application able to detect the walking activity starting only from the data provided by these inertial sensors is a complex task. This complexity lies in the hardware disparity, noise on data, and mostly the many movements that the smartphone can experience and which have nothing to do with the physical displacement of the owner. In this work, we explore and compare several approaches for identifying the walking activity. We categorize them into two main groups: the first one uses features extracted from the inertial data, whereas the second one analyzes the characteristic shape of the time series made up of the sensors readings. Due to the lack of public datasets of inertial data from smartphones for the recognition of human activity under no constraints, we collected data from 77 different people who were not connected to this research. Using this dataset, which we published online, we performed an extensive experimental validation and comparison of our proposals.
  • 946
  • 01 Nov 2020
Topic Review
Vulnerabilities and Potential Threats of Cloud computing
Cloud computing has become a prominent technology due to its important utility service; this service concentrates on outsourcing data to organizations and individual consumers. Cloud computing has considerably changed the manner in which individuals or organizations store, retrieve, and organize their personal information. Despite the manifest development in cloud computing, there are still some concerns regarding the level of security and issues related to adopting cloud computing that prevent users from fully trusting this useful technology.
  • 611
  • 28 Mar 2022
Topic Review
Vulgar Word Extraction in Chittagonian Dialect of Bangla
The proliferation of the internet, especially on social media platforms, has amplified the prevalence of cyberbullying and harassment. Addressing this issue involves harnessing natural language processing (NLP) and machine learning (ML) techniques for the automatic detection of harmful content. However, these methods encounter challenges when applied to low-resource languages like the Chittagonian dialect of Bangla. This entry compares two approaches for identifying offensive language containing vulgar remarks in Chittagonian. The first relies on basic keyword matching, while the second employs machine learning and deep learning techniques. The keyword- matching approach involves scanning the text for vulgar words using a predefined lexicon. Despite its simplicity, this method establishes a strong foundation for more sophisticated ML and deep learning approaches. An issue with this approach is the need for constant updates to the lexicon.
  • 215
  • 17 Nov 2023
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