ArticleComputational intelligence and neuroscience2021
Dynamic Gesture Recognition Algorithm Based on 3D Convolutional Neural Network.
Article in Computational intelligence and neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- Retracted: Dynamic Gesture Recognition Algorithm Based on 3D Convolutional Neural Network.Computational intelligence and neuroscience · 2023Article
- Development and validation of a three-dimensional deep learning-based system for assessing bowel preparation on colonoscopy video.Frontiers in medicine · 2023Article
- Dynamic Hand Gesture Recognition Using Electrical Impedance Tomography.Sensors (Basel, Switzerland) · 2022Article
- Spatial Attention-Based 3D Graph Convolutional Neural Network for Sign Language Recognition.Sensors (Basel, Switzerland) · 2022Article
- Low-Illumination Image Enhancement Algorithm Based on Improved Multi-Scale Retinex and ABC Algorithm Optimization.Frontiers in bioengineering and biotechnology · 2022Article
- Image Classification and Recognition of Rice Diseases: A Hybrid DBN and Particle Swarm Optimization Algorithm.Frontiers in bioengineering and biotechnology · 2022Article
- Multi-Scale Feature Fusion Convolutional Neural Network for Indoor Small Target Detection.Frontiers in neurorobotics · 2022Article
- A Tandem Robotic Arm Inverse Kinematic Solution Based on an Improved Particle Swarm Algorithm.Frontiers in bioengineering and biotechnology · 2022Article
- Genetic-Based Optimization of 3D Burch-Schneider Cage With Functionally Graded Lattice Material.Frontiers in bioengineering and biotechnology · 2022Article
- Attitude Stabilization Control of Autonomous Underwater Vehicle Based on Decoupling Algorithm and PSO-ADRC.Frontiers in bioengineering and biotechnology · 2022Article
- Multi-Stream Convolutional Neural Network-Based Wearable, Flexible Bionic Gesture Surface Muscle Feature Extraction and Recognition.Frontiers in bioengineering and biotechnology · 2022Article
- Improved Multi-Stream Convolutional Block Attention Module for sEMG-Based Gesture Recognition.Frontiers in bioengineering and biotechnology · 2022Article
- Multi-Objective Optimization Design of Ladle Refractory Lining Based on Genetic Algorithm.Frontiers in bioengineering and biotechnology · 2022Article
- Real-Time Target Detection Method Based on Lightweight Convolutional Neural Network.Frontiers in bioengineering and biotechnology · 2022Article
- Dance-Specific Action Recognition Method Based on Double-Stream CNN in Complex Environment.Journal of environmental and public health · 2022Article
- Dynamic Gesture Recognition Using Surface EMG Signals Based on Multi-Stream Residual Network.Frontiers in bioengineering and biotechnology · 2021Article
- Genetic Algorithm-Based Trajectory Optimization for Digital Twin Robots.Frontiers in bioengineering and biotechnology · 2021Article
- Self-Tuning Control of Manipulator Positioning Based on Fuzzy PID and PSO Algorithm.Frontiers in bioengineering and biotechnology · 2021Article
- Intelligent Detection of Steel Defects Based on Improved Split Attention Networks.Frontiers in bioengineering and biotechnology · 2021Article
Corrections and comments
- Retraction · 2023-06-28Concerns/Issues about Data · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gesture recognition is one of the important ways of human-computer interaction, which is mainly detected by visual technology. The temporal and spatial features are extracted by convolution of the video containing gesture. However, compared with the convolution calculation of a single image, multiframe image of dynamic gestures has more computation, more complex feature extraction, and more network parameters, which affects the recognition efficiency and real-time performance of the model. To solve above problems, a dynamic gesture recognition model based on CBAM-C3D is proposed. Key frame extraction technology, multimodal joint training, and network optimization with BN layer are used for making the network performance better. The experiments show that the recognition accuracy of the proposed 3D convolutional neural network combined with attention mechanism reaches 72.4% on EgoGesture dataset, which is improved greatly compared with the current main dynamic gesture recognition methods, and the effectiveness of the proposed algorithm is verified.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.