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Automated Quality Inspection with Vision AIReal-time AI-powered vision system for detecting defects in manufacturing environments
Quality Control -
FFNet for Real-Time Semantic SegmentationLightweight semantic segmentation model optimized for real-time street scene analysis on edge devices.
Quality Control -
YAMNet for Environmental Sound ClassificationReal-time environmental sound classifier optimized for low-power edge devices using MobileNet v1.
Forecasting Operational Optimization -
Time Series Anomaly Detection with Isolation ForestLightweight anomaly detector for time series data using Isolation Forest, designed for edge environments.
Forecasting Operational Optimization -
Image ClassificationEfficient CNN model for image classification on mobile and embedded edge devices.
Quality Control -
Object DetectionFast object detection using YOLOX optimized for embedded edge devices.
Quality Control -
Image Analysis for Defect – Training ExperienceAI-powered image analysis tool for defect detection in industrial environments, with a guided journey for customizing new defect types.
Quality Control -
Scene Text Detection – High AccuracyHigh-precision OCR application that detects and transcribes text from real-world images with superior accuracy, ideal for industrial and logistics use cases.
Quality Control -
Scene Text Detection – Light ModelLightweight OCR application that detects and reads text in images using a faster, lower-resource model designed for embedded and edge devices.
Quality Control -
PCB Defect DetectionSpecialized AI-based vision system for detecting surface and structural defects on printed circuit boards (PCBs) during manufacturing inspection.
Quality Control -
Object detection with RF-DETRAdvanced transformer-based detector optimized for accurate, real-time edge performance on SECO platforms.
Quality Control -
ResNet – Training Experience on DeviceOn-device fine-tuning/validation of ResNet classifiers—customize without cloud dependency.
Quality Control