AIMC Topic: Human Activities

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A human activity recognition model based on deep neural network integrating attention mechanism.

Scientific reports
Human Activity Recognition (HAR) is crucial in multiple fields. Existing HAR techniques include manual feature extraction, codebook-based methods, and deep learning, each with limitations. This paper presents DCAM-Net (DeepConvAttentionMLPNet), a nov...

FSID: a novel approach to human activity recognition using few-shot weight imprinting.

Scientific reports
Accurate recognition of human activities from gait sensory data plays a vital role in healthcare and wellness monitoring. However, conventional deep learning models for Human Activity Recognition (HAR) often require large labeled datasets and extensi...

Intelligent recognition of human activities using deep learning techniques.

PloS one
Recognition of Human Actions (HAR) Portrays a crucial significance in various applications due to its ability for analyzing behaviour of humans within videos. This research investigates HAR in Red, Green, and Blue, or RGB videos using frameworks for ...

Efficient human activity recognition on edge devices using DeepConv LSTM architectures.

Scientific reports
Driven by the rapid development of the Internet of Things (IoT), deploying deep learning models on resource-constrained hardware has become an increasingly critical challenge, which has propelled the emergence of TinyML as a viable solution. This stu...

A Review of AIoT-Based Human Activity Recognition: From Application to Technique.

IEEE journal of biomedical and health informatics
This scoping review paper redefines the Artificial Intelligence-based Internet of Things (AIoT) driven Human Activity Recognition (HAR) field by systematically extrapolating from various application domains to deduce potential techniques and algorith...

Human activity recognition algorithms for manual material handling activities.

Scientific reports
Human Activity Recognition (HAR) using wearable sensors has prompted substantial interest in recent years due to the availability and low cost of Inertial Measurement Units (IMUs). HAR using IMUs can aid both the ergonomic evaluation of the performed...

IoT powered RNN for improved human activity recognition with enhanced localization and classification.

Scientific reports
Human activity recognition (HAR) and localization are green research areas of the modern era that are being propped up by smart devices. But the data acquired from the sensors embedded in smart devices, contain plenty of noise that makes it indispens...

Human Activity Recognition Using Deep Residual Convolutional Network Based on Wearable Sensors.

IEEE journal of biomedical and health informatics
Human activity recognition (HAR) can play a vital role in biomedical and health informatics by enabling the monitoring of human daily activities and health behaviors. Accurate HAR can provide valuable insights into patients' physical activity levels,...

Skeleton Reconstruction Using Generative Adversarial Networks for Human Activity Recognition Under Occlusion.

Sensors (Basel, Switzerland)
Recognizing human activities from motion data is a complex task in computer vision, involving the recognition of human behaviors from sequences of 3D motion data. These activities encompass successive body part movements, interactions with objects, o...

Deep Reinforcement Learning in Human Activity Recognition: A Survey and Outlook.

IEEE transactions on neural networks and learning systems
Human activity recognition (HAR) is a popular research field in computer vision that has already been widely studied. However, it is still an active research field since it plays an important role in many current and emerging real-world intelligent s...