Publications related to Scene Recognition with Naive Bayes Non-linear Learning

Classification of fall directions via wearable motion sensors

Effective fall-detection and classification systems are vital in mitigating severe medical and economical consequences of falls to people in the fall risk groups. One class of such systems is based on wearable sensors. While there is a vast amount of acade ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Nahal Mansouri, Sahand Jamal Rahi

Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.Objecti ...

FRONTIERS MEDIA SA2022

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Alexandre Schmid, Keyvan Farhang Razi

Early and accurate detection of epileptic seizures is an extremely important therapeutic goal due to the severity of complications it can prevent. To this end, a low-power machine learning-based seizure detection implemented on an FPGA is proposed in this ...

IEEE2022

Identifying uncertainty states during wayfinding in indoor environments: An EEG classification Study

Mahsa Shoaran, Bingzhao Zhu

The researchers used a machine-learning classification approach to better understand neurological features associated with periods of wayfinding uncertainty. The participants (n = 30) were asked to complete wayfinding tasks of varying difficulty in a virtu ...

ELSEVIER SCI LTD2022

Predicting Superagers by Machine Learning Classification Based on the Functional Brain Connectome Using Resting-State Functional Magnetic Resonance Imaging

Chang-Hyun Park

Superagers are defined as older adults who have youthful memory performance comparable to that of middle-aged adults. Classifying superagers based on the brain connectome using machine learning modeling can provide important insights on the physiology unde ...

OXFORD UNIV PRESS INC2021

Using footstep-induced vibrations for occupant detection and recognition in buildings

Ian Smith, Yves Sylvain Gilles Reuland, Sai Ganesh Sarvotham Pai, Slah Drira

Occupant detection and recognition support functional goals such as security, healthcare, and energy management in buildings. Typical sensing approaches, such as smartphones and cameras, undermine the privacy of building occupants and inherently affect the ...

2021

Parametrized classifiers for optimal EFT sensitivity

Andrea Wulzer, Alfredo Glioti, Siyu Chen

We study unbinned multivariate analysis techniques, based on Statistical Learning, for indirect new physics searches at the LHC in the Effective Field Theory framework. We focus in particular on high-energy ZW production with fully leptonic decays, modeled ...

SPRINGER2021

Evading Voltage-Based Intrusion Detection on Automotive CAN

Mathias Josef Payer, Duo Xu, Rohit Bhatia

The controller area network (CAN) is widely adopted in modern automobiles to enable communications among in-vehicle electronic control units (ECUs). Lacking mainstream network security capabilities due to resource constraints, the CAN is susceptible to the ...

INTERNET SOC2021

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Scene Recognition with Naive Bayes Non-linear Learning

Data-driven approaches for non-invasive cuffless blood pressure monitoring

Classification of fall directions via wearable motion sensors

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

On Generalizations of Some Distance Based Classifiers for HDLSS Data

Identifying uncertainty states during wayfinding in indoor environments: An EEG classification Study

Predicting Superagers by Machine Learning Classification Based on the Functional Brain Connectome Using Resting-State Functional Magnetic Resonance Imaging

Using footstep-induced vibrations for occupant detection and recognition in buildings

Parametrized classifiers for optimal EFT sensitivity

Evading Voltage-Based Intrusion Detection on Automotive CAN

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Chat with Graph Search

Data-driven approaches for non-invasive cuffless blood pressure monitoring

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Identifying uncertainty states during wayfinding in indoor environments: An EEG classification Study

Predicting Superagers by Machine Learning Classification Based on the Functional Brain Connectome Using Resting-State Functional Magnetic Resonance Imaging

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Classification of fall directions via wearable motion sensors

On Generalizations of Some Distance Based Classifiers for HDLSS Data

Using footstep-induced vibrations for occupant detection and recognition in buildings

Parametrized classifiers for optimal EFT sensitivity

Evading Voltage-Based Intrusion Detection on Automotive CAN