Convae-lstm: Convolutional autoencoder long short-term memory network for smartphone-based human activity recognition
The self-regulated recognition of human activities from time-series smartphone sensor data
is a growing research area in smart and intelligent health care. Deep learning (DL) …
is a growing research area in smart and intelligent health care. Deep learning (DL) …
Improved soccer action spotting using both audio and video streams
In this paper, we propose a study on multi-modal (audio and video) action spotting and
classification in soccer videos. Action spotting and classification are the tasks that consist in …
classification in soccer videos. Action spotting and classification are the tasks that consist in …
Attention-based multihead deep learning framework for online activity monitoring with smartwatch sensors
The expeditious propagation of Internet of Things (IoT) technologies implanted in different
smart devices, such as smartphones and smartwatches have a ubiquitous consequence on …
smart devices, such as smartphones and smartwatches have a ubiquitous consequence on …
Human action recognition using deep learning methods
Z Yu, WQ Yan - 2020 35th International Conference on Image …, 2020 - ieeexplore.ieee.org
The goal of human action recognition is to identify and understand the actions of people in
videos and export corresponding tags. In addition to spatial correlation existing in 2D …
videos and export corresponding tags. In addition to spatial correlation existing in 2D …
Short-term forecasting of satellite-based drought indices using their temporal patterns and numerical model output
Drought forecasting is essential for effectively managing drought-related damage and
providing relevant drought information to decision-makers so they can make appropriate …
providing relevant drought information to decision-makers so they can make appropriate …
Two-stream convolutional neural network based on gradient image for aluminum profile surface defects classification and recognition
C Duan, T Zhang - IEEE access, 2020 - ieeexplore.ieee.org
In this article, a novel two-stream convolutional neural network based on gradient image is
performed to effectively classify and identify aluminum profiles defects for the first time …
performed to effectively classify and identify aluminum profiles defects for the first time …
Two-stream convolutional long-and short-term memory model using perceptual loss for sequence-to-sequence Arctic sea ice prediction
Arctic sea ice plays a significant role in climate systems, and its prediction is important for
co** with global warming. Artificial intelligence (AI) has gained recent attention in various …
co** with global warming. Artificial intelligence (AI) has gained recent attention in various …
Transformer-based spatial–temporal detection of apoptotic cell death in live-cell imaging
Intravital microscopy has revolutionized live-cell imaging by allowing the study of spatial–
temporal cell dynamics in living animals. However, the complexity of the data generated by …
temporal cell dynamics in living animals. However, the complexity of the data generated by …
A critical study on the recent deep learning based semi-supervised video anomaly detection methods
Video anomaly detection (VAD) is currently a trending research area within computer vision,
given that anomalies form a key detection objective in surveillance systems, often requiring …
given that anomalies form a key detection objective in surveillance systems, often requiring …
[HTML][HTML] Next-Gen Dynamic Hand Gesture Recognition: MediaPipe, Inception-v3 and LSTM-Based Enhanced Deep Learning Model
Gesture recognition is crucial in computer vision-based applications, such as drone control,
gaming, virtual and augmented reality (VR/AR), and security, especially in human–computer …
gaming, virtual and augmented reality (VR/AR), and security, especially in human–computer …