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Human Activities

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The SESAME Human-Earth Atlas.

Scientific data
Human activities such as food production, mining, transportation, and construction have extensively modified Earth's land and marine environments, causing biodiversity loss, water pollution, soil erosion, and climate change. However, studying spatial...

Enhanced In-Home Human Activity Recognition Using Multimodal Sensing and Spatiotemporal Machine Learning Architecture.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this research, we present an enhanced human activity recognition (HAR) framework using advanced machine learning models incorporating temporal dynamics, leveraging multimodal sensor data. Data from wearable wristbands and real-time location system...

Deep Learning-Based Subject Independent Human Activity Recognition using Smart Lacelock Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Human Activity Recognition (HAR) field is rapidly growing and the classification of human activities based on sensor data is crucial for applications in healthcare, rehabilitation and numerous other sectors. In this paper we use a novel device and at...

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 ...

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...

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...

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,...

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...

Robust two stages federated learning for sensor based human activity recognition with label noise.

Scientific reports
Federated learning is widely used for collaborative training of human activity recognition models across multiple devices with limited local data. However, label noise caused by human and time constraints during data annotation is common and severely...