Automated building extraction from satellite images is widely used for urban planning, disaster management, and many other applications, which is a challenging research problem due to its variability. Edge information...
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With the rapid development of autonomous driving technology, public's opinion of this technology shows diversification and complexity. The discussion about autonomous driving online has a large quantity and divers...
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Air quality emerges as a critical global concern affecting millions of individuals. This paper explores into the development and application of data-driven models for air quality prediction, Motivated by air quality&#...
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This research study reviews the quantum kernel techniques and discusses about the application of a quantum machine learning model for the classification of breast cancer using Qiskit Machine learning version 0.4.0. Th...
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As digital transformation accelerates world-wide, digital forensics has become increasingly crucial in storing and administering digital evidence during forensic investigations. Although digital forensics provides a s...
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A specialized virtual reality platform, designed for desktop use, has emerged to assist in the recovery of stroke patients' impaired limbs. The proposed system integrates a mixed reality headset for computational ...
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Identifying human actions and interactions finds its use in manyareas, such as security, surveillance, assisted living, patient monitoring, rehabilitation,sports, and e-learning. This wide range of applications has at...
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Identifying human actions and interactions finds its use in manyareas, such as security, surveillance, assisted living, patient monitoring, rehabilitation,sports, and e-learning. This wide range of applications has attractedmany researchers to this field. Inspired by the existing recognition systems,this paper proposes a new and efficient human-object interaction recognition(HOIR) model which is based on modeling human pose and scene featureinformation. There are different aspects involved in an interaction, includingthe humans, the objects, the various body parts of the human, and the backgroundscene. Themain objectives of this research include critically examiningthe importance of all these elements in determining the interaction, estimatinghuman pose through image foresting transform (IFT), and detecting the performedinteractions based on an optimizedmulti-feature vector. The proposedmethodology has six main phases. The first phase involves preprocessing theimages. During preprocessing stages, the videos are converted into imageframes. Then their contrast is adjusted, and noise is removed. In the secondphase, the human-object pair is detected and extracted from each image *** third phase involves the identification of key body parts of the detectedhumans using IFT. The fourth phase relates to three different kinds of featureextraction techniques. Then these features are combined and optimized duringthe fifth phase. The optimized vector is used to classify the interactions in thelast phase. TheMSRDaily Activity 3D dataset has been used to test this modeland to prove its efficiency. The proposed system obtains an average accuracyof 91.7% on this dataset.
Edge computing has emerged as a crucial paradigm to fulfill the increasing demand for rapid data processing, low latency, and efficient resource utilization, particularly in applications such as the Internet of Things...
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Segmentation of camouflaged objects presents a significant challenge in computer vision due to their inherent blending with the background environment. This study proposes an innovative method for precise camouflage s...
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In this paper, we deal with the problem of estimating the Direction of Arrival (DOA) of vehicles under the interference assumption in frequency division multiplexing-multiple input-multiple output (FDM-MIMO) Automotiv...
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