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Topic Review
Voting-Based Leader-Election Scheme in Lead-Follow UAV Swarm
The recent advances in unmanned aerial vehicles (UAVs) enormously improve their utility and expand their application scope. The UAV and swarm implementation further prevail in Smart City practices with the aid of edge computing and urban Internet of Things. The lead–follow formation in UAV swarm is an important organization means and has been adopted in diverse exercises, for its efficiency and ease of control. The reliability of centralization makes the entire swarm system in risk of collapse and instability, if a fatal fault incident happens in the leader. Researchers propose a voting-based leader election scheme inspired by the Raft method in distributed computation consensus to build a mechanism helping the distributed swarm recover from possible failures.
  • 447
  • 15 Aug 2022
Topic Review
Visual Tracking Related to Age or Gender Information
Visual tracking of multiple targets, also referred to as multiple object tracking (MOT), since the target can be any moving object or entity, is a well-investigated computer vision task. Actually, the goal is to detect one or more targets in a time-variate scene and then obtain their trajectories in terms of following their tracklets, for a given video sequence. This is completed by associating newly detected instances with current ones. Typically, the association part assumes a prediction task whose aim is to favor the most possible correspondence among detections of consecutive frames for a given target. When the targets of interest are real people, resulting detections from this procedure are usually post-processed so as to extract useful information related, for instance, with their age or gender. 
  • 122
  • 11 Dec 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.
  • 558
  • 30 Dec 2022
Topic Review
Visual Question Answering
Visual question answering (VQA) is a task that generates or predicts an answer to a question in human language about visual images. VQA is an active field combining two AI branches: Natural language processing (NLP) and computer vision. VQA usually has four components: vision featurization, text featurization, fusion model, and classifier. Vision featurization is a part of the multi-model responsible for extracting the vision features. Text featurization is another part of the VQA multi-model responsible for extracting text features. The combination of both features and their processes is the fusion component. The last component is the classifier that classifies the queries about the images and generates the answer.
  • 928
  • 22 Sep 2023
Topic Review
Vision-Based Pose Estimation of Non-Cooperative Target
In the realm of non-cooperative space security and on-orbit service, a significant challenge is accurately determining the pose of abandoned satellites using imaging sensors. Traditional methods for estimating the position of the target encounter problems with stray light interference in space, leading to inaccurate results.
  • 141
  • 18 Dec 2023
Topic Review
Vision-Based Human Action Recognition Field
Artificial intelligence’s rapid advancement has enabled various applications, including intelligent video surveillance systems, assisted living, and human–computer interaction. These applications often require one core task: video-based human action recognition.
  • 275
  • 23 Apr 2023
Topic Review
Vision-Based Gait Recognition
Identifying people’s identity by using behavioral biometrics has attracted many researchers’ attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait recognition has been performed by using handcrafted approaches. Due to several covariates’ effects, the competence of the approach has been compromised. Deep learning is an emerging algorithm in the biometrics field, which has the capability to tackle the covariates and produce highly accurate results. 
  • 337
  • 12 Aug 2022
Topic Review
Vision-Based Flying Obstacle Detection for Avoiding Midair Collisions
See and avoid is a basic procedure that pilots must learn and apply during flight. Various technologies have been introduced to avoid midair collisions, but accidents still occur because they are neither mandatory in all airspaces nor suitable for all aircraft.
  • 117
  • 26 Oct 2023
Topic Review
Vision-Based Autonomous Vehicle Systems
Autonomous vehicle systems (AVS) have advanced at an exponential rate, particularly due to improvements in artificial intelligence, which have had a significant impact on social as well as road safety and the future of transportation systems. Deep learning is fast becoming a successful alternative approach for perception-based AVS as it reduces both cost and dependency on sensor fusion.
  • 787
  • 12 Jul 2022
Topic Review
Vision-Autocorrect
The last two years have seen a rapid rise in the duration of time that both adults and children spend on screens, driven by the recent COVID-19 health pandemic. A key adverse effect is digital eye strain (DES). Recent trends in human-computer interaction and user experience have proposed voice or gesture-guided designs that present more effective and less intrusive automated solutions. These approaches inspired the design of a solution that uses facial expression recognition (FER) techniques to detect DES and autonomously adapt the application to enhance the user’s experience.
  • 202
  • 23 Nov 2023
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