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Trans-Neu-Pest combines Swin Transformer and 3D reconstruction to spot camouflaged pests with 93.1% precision while running on low-power neuromorphic hardware.

Researchers propose brain-like spiking neural networks and compute-in-memory hardware as the key to overcoming the massive energy bottleneck stifling sustainable AI advancement.