Due to the widespread applications and potential security risks, unmanned aerial vehicle (UAV) detection has received increasing attention in recent years. Among the various methods, one promising method is wireless s...
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Ensuring the authenticity and integrity of digital images is a major concern in multimedia forensics, driving research on universal schemes for detecting diverse image manipulations (or processing operations). Althoug...
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With an association of principles created to improve collaboration amidst the operations and development teams, DevOps offers few agile practices. The paper's main goal is to conduct research about how the practic...
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In recent years, research combining max pressure (MP) with reinforcement learning for traffic signal control has become a hot topic in the field of intelligent transportation. However, existing MP methods ignore the i...
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Class imbalance is a frequently occurring issue in predictive modeling. Learning from imbalanced data is a challenging task that has attracted much interest from scholars. While a substantial amount of research has be...
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In this study, we investigate a traffic monitoring method to detect passing cars, bikes, and humans from roadsides using millimeter-wave radar during road work. Because a road worker is one of the most dangerous occup...
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In this era, Peer-to-Peer (P2P) networks have developed as a revolutionized network for data distribution and alternate to traditional client-server network. The features of P2P networks allow a distributed group of u...
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Human Pose Estimation (HPE) aims to predict the positional coordinates of body keypoints in images. While significant progress has been made in HPE, certain challenges persist. For example, the potential for robust oc...
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Fluorescence nanoscopy provides imaging techniques that overcome the diffraction-limited resolution barrier in light microscopy,thereby opening up a new area of research in biomedical imaging in fields such as ***,we ...
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Fluorescence nanoscopy provides imaging techniques that overcome the diffraction-limited resolution barrier in light microscopy,thereby opening up a new area of research in biomedical imaging in fields such as ***,we review the foremost fluorescence nanoscopy techniques,including descriptions of their applications in elucidating protein architectures and mobility,the real-time determination of synaptic parameters involved in neural processes,three-dimensional imaging,and the tracking of nanoscale neural *** conclude by discussing the prospects of fluorescence nanoscopy,with a particular focus on its deployment in combination with related techniques(e.g.,machine learning)in neuroscience.
Smoking has an economic and environmental impact on society due to the toxic substances it *** Neural Networks(CNNs)need help describing low-level features and can miss important ***,accurate smoker detection is vital...
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Smoking has an economic and environmental impact on society due to the toxic substances it *** Neural Networks(CNNs)need help describing low-level features and can miss important ***,accurate smoker detection is vital with minimum false *** answer the issue,the researchers of this paper have turned to a self-attention mechanism inspired by the ViT,which has displayed state-of-the-art performance in the classification *** effectively enforce the smoking prohibition in non-smoking locations,this work presents a Vision Transformer-inspired model called SmokerViT for detecting ***,this research utilizes a locally curated dataset of 1120 images evenly distributed among the two classes(Smoking and NotSmoking).Further,this research performs augmentations on the smoker detection dataset to have many images with various representations to overcome the dataset size *** convolutional operations used in most existing works,the proposed SmokerViT model employs a self-attention mechanism in the Transformer block,making it suitable for the smoker classification ***,this work integrates the multi-layer perceptron head block in the SmokerViT model,which contains dense layers with rectified linear activation and linear kernel regularizer with L2 for the recognition *** work presents an exhaustive analysis to prove the efficiency of the proposed SmokerViT *** performance of the proposed SmokerViT performance is evaluated and compared with the existing methods,where it achieves an overall classification accuracy of 97.77%,with 98.21%recall and 97.35%precision,outperforming the state-of-the-art deep learning models,including convolutional neural networks(CNNs)and other vision transformer-based models.
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