This paper investigates the influence of a static robot head on deviations of human hand movements from task direction (motor interference) during simultaneous human and robot arm movements using a collaborative robot...
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Connecting multiple aerial vehicles to a rigid central platform through passive spherical joints holds the potential to construct a fully-actuated aerial platform. The integration of multiple vehicles enhances efficie...
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Control and curation of dominant visual culture - rendering who and what is visible - is central to identity formation, particularly for LGBTQ+ communities relying on digital spaces for safe self-expression. In this w...
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Breast cancer is one of the major health issues with high mortality rates and a substantial impact on patients and healthcare systems *** computer-Aided Diagnosis(CAD)tools,based on breast thermograms,have been develo...
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Breast cancer is one of the major health issues with high mortality rates and a substantial impact on patients and healthcare systems *** computer-Aided Diagnosis(CAD)tools,based on breast thermograms,have been developed for early detection of this ***,accurately segmenting the Region of Interest(ROI)fromthermograms remains *** paper presents an approach that leverages image acquisition protocol parameters to identify the lateral breast region and estimate its bottomboundary using a second-degree *** proposed method demonstrated high efficacy,achieving an impressive Jaccard coefficient of 86%and a Dice index of 92%when evaluated against manually created ground *** features were extracted from each view’s ROI,with significant features selected via Mutual Information for training Multi-Layer Perceptron(MLP)and K-Nearest Neighbors(KNN)*** findings revealed that the MLP classifier outperformed the KNN,achieving an accuracy of 86%,a specificity of 100%,and an Area Under the Curve(AUC)of *** consistency of the method across both sides of the breast suggests its viability as an auto-segmentation ***,the classification results suggests that lateral views of breast thermograms harbor valuable features that can significantly aid in the early detection of breast cancer.
Various applications, including space exploration, transportation, factories, and the military, demand the presence of mobile robots. In those applications, navigation algorithms are essential for enabling mobile robo...
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The interpretability of deep learning models has emerged as a compelling area in artificial intelligence *** safety criteria for medical imaging are highly stringent,and models are required for an ***,existing convolu...
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The interpretability of deep learning models has emerged as a compelling area in artificial intelligence *** safety criteria for medical imaging are highly stringent,and models are required for an ***,existing convolutional neural network solutions for left ventricular segmentation are viewed in terms of inputs and ***,the interpretability of CNNs has come into the *** medical imaging data are limited,many methods to fine-tune medical imaging models that are popular in transfer models have been built using massive public Image Net datasets by the transfer learning ***,this generates many unreliable parameters and makes it difficult to generate plausible explanations from these *** this study,we trained from scratch rather than relying on transfer learning,creating a novel interpretable approach for autonomously segmenting the left ventricle with a cardiac *** enhanced GPU training system implemented interpretable global average pooling for graphics using deep *** deep learning tasks were *** included data management,neural network architecture,and *** system monitored and analyzed the gradient changes of different layers with dynamic visualizations in real-time and selected the optimal deployment *** results demonstrated that the proposed method was feasible and efficient:the Dice coefficient reached 94.48%,and the accuracy reached 99.7%.It was found that no current transfer learning models could perform comparably to the ImageNet transfer learning *** model is lightweight and more convenient to deploy on mobile devices than transfer learning models.
Advancement in marine vessel stabilization technologies has greatly improved the safety and comfort for crews, cargo, and passengers, while also lowering the risk of capsizing. Marine vessels operating in open waters ...
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This paper introduces a novel approach for enabling real-time imitation of human head motion by a Nao robot, with a primary focus on elevating human-robot interactions. By using the robust capabilities of the MediaPip...
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In this paper, we explore how robots can properly explain failures during navigation tasks with privacy concerns. We present an integrated robotics approach to generate visual failure explanations, by combining a lang...
In this paper, we explore how robots can properly explain failures during navigation tasks with privacy concerns. We present an integrated robotics approach to generate visual failure explanations, by combining a language-capable cognitive architecture (for recognizing intent behind commands), an object- and location-based context recognition system (for identifying the locations of people and classifying the context in which those people are situated) and an infeasibility proof-based motion planner (for explaining planning failures on the basis of contextually mediated privacy concerns). The behavior of this integrated system is validated using a series of experiments in a simulated medical environment.
Brain-computer interfaces (BCIs) offer promising solutions for upper limb rehabilitation. Despite advancements in deep learning, traditional models for motor rehabilitation using electroencephalography (EEG) or electr...
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