Optimal Training Configurations of a CNN-LSTM-Based Tracker for a Fall Frame Detection System
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Optimal Training Configurations of a CNN-LSTM-Based Tracker for a Fall Frame Detection System
Authors
Keywords
-
Journal
SENSORS
Volume 21, Issue 19, Pages 6485
Publisher
MDPI AG
Online
2021-09-29
DOI
10.3390/s21196485
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Classification of Indoor Human Fall Events Using Deep Learning
- (2021) Arifa Sultana et al. Entropy
- Detection of price bubbles in Istanbul housing market using LSTM autoencoders: a district-based approach
- (2021) Ebubekir Ayan et al. Soft Computing
- A Feasibility Study of the Use of Smartwatches in Wearable Fall Detection Systems
- (2021) Francisco Javier González-Cañete et al. SENSORS
- Real time fall detection using infrared cameras and reflective tapes under day/night luminance
- (2021) E. Ramanujam et al. Journal of Ambient Intelligence and Smart Environments
- Neural machine translation with Gumbel Tree-LSTM based encoder
- (2020) Chao Su et al. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
- Transductive LSTM for time-series prediction: An application to weather forecasting
- (2020) Zahra Karevan et al. NEURAL NETWORKS
- A novel real-time fall detection method based on head segmentation and convolutional neural network
- (2020) Chenguang Yao et al. Journal of Real-Time Image Processing
- A Framework for Fall Detection Based on OpenPose Skeleton and LSTM/GRU Models
- (2020) Chuan-Bi Lin et al. Applied Sciences-Basel
- The Impact of Discontinuation of the Medical Examiner System: Cases of Drowning in the Bathtub at Home
- (2019) Yasuhiro Kakiuchi et al. JOURNAL OF FORENSIC SCIENCES
- Abnormal behavior recognition for intelligent video surveillance systems: A review
- (2018) Amira Ben Mabrouk et al. EXPERT SYSTEMS WITH APPLICATIONS
- Deep Learning for Computer Vision: A Brief Review
- (2018) Athanasios Voulodimos et al. Computational Intelligence and Neuroscience
- Detection of Human Falls on Furniture Using Scene Analysis Based on Deep Learning and Activity Characteristics
- (2018) Weidong Min et al. IEEE Access
- Ambient assistance service for fall and heart problem detection
- (2018) Amina Makhlouf et al. Journal of Ambient Intelligence and Humanized Computing
- Detection of abnormal behavior in narrow scene with perspective distortion
- (2018) Jin Zhang et al. MACHINE VISION AND APPLICATIONS
- Multiple-Model Fully Convolutional Neural Networks for Single Object Tracking on Thermal Infrared Video
- (2018) Mohd Asyraf Zulkifley et al. IEEE Access
- Automatic Fall Detection Using Membership Based Histogram Descriptors
- (2017) Mohamed Maher Ben Ismail et al. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
- Artificial Intelligence in Precision Cardiovascular Medicine
- (2017) Chayakrit Krittanawong et al. JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
- Review of fall detection techniques: A data availability perspective
- (2017) Shehroz S. Khan et al. MEDICAL ENGINEERING & PHYSICS
- Vision-Based Fall Detection with Convolutional Neural Networks
- (2017) Adrián Núñez-Marcos et al. WIRELESS COMMUNICATIONS & MOBILE COMPUTING
- Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification
- (2013) Imen Charfi et al. JOURNAL OF ELECTRONIC IMAGING
- Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches
- (2012) Mohd Zulkifley et al. SENSORS
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now