⚠️ Important Notice

This model is provided for evaluation and development purposes only. It is not validated for and must not be used in clinical, diagnostic, or production settings. See #use-and-limitations.


Model Information

Description

latch-detect is a single-stage object detection model that detects the latch clips on the corners of a NICU radiant warmer hood. It uses the same MobileNetV2 + FPN + anchor-free head architecture as the companion person and patient detection models, retrained to recognize warmer latch hardware. Downstream logic infers the warmer hood state: one or more detected clips indicates the hood is closed/latched; zero detections indicates it is open/unlatched. Asymmetric hysteresis (2 consecutive open readings to open, 3 to close) is applied in the application layer for stability. This model is a development and evaluation tool produced as part of Intel's NICU Warmer reference design and has not undergone clinical validation.

Intended Use

This model is intended for use by software developers and researchers evaluating AI-assisted equipment-state monitoring in a NICU context on Intel hardware. It demonstrates detection of small mechanical features (latch clips) in warmer video as a proxy for hood-closed/open status. latch-detect itself does not provide any medical functionality, nor is it intended to process or interpret medical data for a medical purpose. Developers are responsible for independently validating and adapting latch-detect for their specific use case. It must not be used in live clinical environments or relied upon for patient-safety decisions.


Technical Specifications

Attribute Detail
Architecture MobileNetV2 backbone + FPN neck + anchor-free detection head
Parameters ~5–7M (FP32)
Input 992×800 RGB image (W×H), float32, normalized [0,1], NCHW
Output [N, 5] — bounding boxes (x1, y1, x2, y2, confidence), post-NMS, pixel coords at input resolution; application layer counts detections to classify hood state as "open" or "closed
Training hardware Intel Ultra Core
Framework PyTorch (mmdetection) → OpenVINO IR FP32

Use and Limitations

Permitted Uses

  • Evaluation and benchmarking of Healthcare and Life Sciences AI workflows
  • Research and development
  • Academic study
  • Adaptation and modification for non-clinical applications

Prohibited Uses

  • Clinical or diagnostic use
  • Production deployment without independent validation and applicable regulatory authorization
  • Use with live patients or real patient data (unless the user has obtained all necessary authorizations)
  • Any use that would cause Intel to be treated as the manufacturer, provider, or deployer of a medical device or regulated AI system

License

The use of latch-detect is governed by the Intel Limited Internal Research & Development Use License Agreement. By accessing this model, you agree to the license terms.

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