Resource Hub

Improving accuracy of respiratory rate estimation by restoring high resolution features with transformers and recursive convolutional models

June 25, 2021
Alicja Kwasniewska
Technical Paper
Share on:

Stay Up to Date with the Latest from SiMa.ai

Sign-up

Improving accuracy of respiratory rate estimation by restoring high resolution features with transformers and recursive convolutional models

Related Resources

Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth

Multi-Sensor Ensemble-Guided Attention Network for Aerial Vehicle Perception Beyond Visible Spectrum

On the Importance of Sign Labeling: The Hamburg Sign Language Notation System Case Study

Can AI see bias in X-ray images?

Machine Learning at the Edge: UAV Automatic Takeoff and Landing

Comparison of image pre-processing methods in liver segmentation task

Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems

AI-Based Rotation Aware Detection of Aircraft and Identification of Key Features for Collision Avoidance Systems

Fully Automated AI-powered Contactless Cough Detection based on Pixel Value Dynamics Occurring within Facial Regions

Take Charge of Accelerating your Edge AI Journey

Talk to an Expert