Convolutional Neural Networks (CNNs) & ResNet
Spatial Translation Invariance, 2D Kernels, Receptive Fields & Residual Skip Connections
#Computer Vision#CNN#Convolutions#ResNet#Feature Maps#Computer Vision
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STAGE 1 / 7— Anti-Pattern
Section 1: The LLM Anti-Pattern vs Right-Sized Model
The Naive Generative LLM Approach:
Calling a multimodal LLM API to detect whether an industrial manufacturing part on an assembly line has a physical crack defect.
Why It Fails in Production:
Costs $0.02 per image, takes 1,500ms over network latency, and cannot guarantee pixel-precise spatial localization. A fine-tuned MobileNet or ResNet runs in 3ms on edge hardware.
Targeted Algorithm (Convolutional Neural Networks (CNNs) & ResNet)
Latency:3ms (ONNX on Edge CPU/NPU)
Cost / 1M Ops:$0.00
Determinism:100% Deterministic Feature Maps
Generative LLM Alternative
Latency:2,000ms
Cost / 1M Ops:$20,000
Determinism:Hallucinated Defect Reports