Pose-Invariant Dog Head Detector

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• InceptionV1 implements a four-layer circuit for pose-invariant dog head detection with mirrored left/right pathways that inhibit each other then unite, exhibiting XOR-like propertiesfinding0.757
  Evidence that neural networks learn sophisticated invariance mechanisms through structured circuits rather than loose feature aggregation
• Symmetry detectorconcept0.718
  Functional role of SOHMs, detecting symmetries in input to compress information.
• Curve Detectorconcept0.683
  A family of neurons found in every non-trivial vision model that detect curved lines in different orientations; primary example used to demonstrate feature understanding
• High-Low Frequency Detectorconcept0.678
  A less intuitive feature family detecting low-frequency patterns on one side of the receptive field and high-frequency on the other; used as example of non-obvious but understandable features
• Consciousness Detectionconcept0.674
  Current research focus in literature; contrasted with the need for systematic introspective processes.
• PET Imagingmethod0.672
  Used by Zubieta et al. to demonstrate actual µ-opioid release during placebo
• InceptionV1 spreads car feature from a pure car detector in mixed4c across dog detector neurons in the next layerfinding0.665
  Circuit-level evidence that polysemantic neurons arise deliberately through superposition rather than entangled computation
• attention head localization analysismethod0.664
  Analysis measuring whether each attention head's maximum attention increase points to the correct injected sentence