Surveillance

Cross-Domain Traffic Scene Understanding by Integrating Deep Learning and Topic Model.

Understanding cross-domain traffic scenarios from multicamera surveillance network is important for environmental perception. Most of existing methods select the source domain which is most similar to the target domain by comparing entire domains for cross-domain similarity and then transferring the motion model learned in the source domain to the target domain. The cross-domain similarity between...

Investigating the Impact of Information Sharing in Human Activity Recognition.

The accuracy of Human Activity Recognition is noticeably affected by the orientation of smartphones during data collection. This study utilized a public domain dataset that was specifically collected to include variations in smartphone positioning. Although the dataset contained records from various sensors, only accelerometer data were used in this study; thus, the developed methodology would pre...

Efficient Violence Detection in Surveillance.

Intelligent video surveillance systems are rapidly being introduced to public places. The adoption of computer vision and machine learning techniques ...

A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance.

This paper presents a comprehensive overview of current deep-learning methods for automatic object classification of underwater sonar data for shoreli...

Deep-learning model for predicting the survival of rectal adenocarcinoma patients based on a surveillance, epidemiology, and end results analysis.

BACKGROUND: We collected information on patients with rectal adenocarcinoma in the United States from the Surveillance, Epidemiology, and EndResults (...

On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer.

Early detection and mitigation of disease recurrence in non-small cell lung cancer (NSCLC) patients is a nontrivial problem that is typically addresse...

Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools.

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular...

A machine learning-based on-demand sweat glucose reporting platform.

Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause ...

Deep learning models for triaging hospital head MRI examinations.

The growing demand for head magnetic resonance imaging (MRI) examinations, along with a global shortage of radiologists, has led to an increase in the...

Robot-assisted Total Mesorectal Excision and Lateral Pelvic Lymph Node Dissection for Locally Advanced Middle-low Rectal Cancer.

Since their approval for clinical use, da Vinci surgical robots have shown great advantages in gastrointestinal surgical operations, especially in com...

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized...

Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant ...

Robot-Assisted Simple Prostatectomy Endoscopic Enucleation of the Prostate: A Systematic Review and Meta-Analysis of Comparative Trials.

Robot-assisted simple prostatectomy (RASP) and endoscopic enucleation of the prostate (EEP) are two minimally invasive alternatives to simple prostat...

Quality in MR reporting of the prostate – improving acquisition, the role of AI and future perspectives.

The high quality of MRI reporting of the prostate is the most critical component of the service provided by a radiologist. Prostate MRI structured rep...

The BMS-LM ontology for biomedical data reporting throughout the lifecycle of a research study: From data model to ontology.

Biomedical research data reuse and sharing is essential for fostering research progress. To this aim, data producers need to master data management an...

Deep learning via LSTM models for COVID-19 infection forecasting in India.

The COVID-19 pandemic continues to have major impact to health and medical infrastructure, economy, and agriculture. Prominent computational and mathe...

Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients.

Acute coronary syndromes (ACS) are a leading cause of deaths worldwide, yet the diagnosis and treatment of this group of diseases represent a signific...

CNN Deep Learning with Wavelet Image Fusion of CCD RGB-IR and Depth-Grayscale Sensor Data for Hand Gesture Intention Recognition.

Pixel-based images captured by a charge-coupled device (CCD) with infrared (IR) LEDs around the image sensor are the well-known CCD Red-Green-Blue IR ...

SF-CNN: Signal Filtering Convolutional Neural Network for Precipitation Intensity Estimation.

Precipitation intensity estimation is a critical issue in the analysis of weather conditions. Most existing approaches focus on building complex model...

Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review.

This paper aims to provide a review of the electrically assisted bicycles (also known as e-bikes) used for recovery of the rider's physical and physio...