Multi-Touch Functionality in Mobile Phones

Technical overview of multi-touch technology: multi-point input, gesture recognition, and common implementations (LLP, FTIR, optical) for interactive displays.

Biometric Identification for IoT Dog Management

Analysis of Chongqing dog registration and pet microchip policies, comparing low-frequency RFID and biometric methods for canine identification and traceability.

Gesture Sensing with ams TMG4903 Optical Module

Overview of non-contact gesture recognition for wearables, comparing the ams TMG4903 optical sensing module and a low-cost breakout board for prototyping.

Advantages of Face Recognition vs Fingerprint Recognition

Overview of face recognition systems: biometric image-processing, real-time 3D identification, template storage and access control, with comparison to fingerprint recognition.

How License Plate Recognition Works

Overview of license plate recognition: image preprocessing, plate localization, character segmentation and recognition, and applications in traffic management.

Balancing Sensitivity and Noise Immunity in Touch ICs

Analysis of touch IC market and design trends: cost pressures, interference and noise-immunity trade-offs, sensitivity, wearables support and HotKnot interaction.

How to Tell Resistive vs Capacitive Touchscreens

Comparison of resistive touchscreen and capacitive touchscreen structures, detection methods, calibration, durability, visibility, and cost for device engineers.

Is an Unresponsive Touchscreen Caused by the Outer or Inner Screen?

Guide to diagnosing touchscreen failure and recovery: causes, impacts, troubleshooting steps (clean, restart, update) and when to seek professional repair.

Face Recognition: How It Works, Pros, Cons, Differences

Technical overview of face recognition: principles of feature extraction and matching, advantages and limitations, and key differences from image recognition.

Stretchable Multichannel sEMG Array for Gesture Recognition

Stretchable bipolar sEMG electrode array with onboard Bluetooth and a graph neural network (GNN) using self-attention to classify 18 static and dynamic gestures.