Table 7.

Computational profile of the shared CNN backbone (FP16 weights; batch-16 inference measured on CPU and on an NVIDIA A100 GPU).

Metric	Value
Computational cost
Total parameters	107,076 (106,052 trainable + 1,024 non-trainable)
Floating-point operations per image	≈879.4 million FLOPs (≈440 million MACs)
Weight memory (FP16)	0.20 MB
Inference time (CPU)
Latency per image	42.2 ms (median); 41.5 ms (minimum)
Throughput	23.7 images/s
Inference time (GPU)
Latency per image	4.54 ms (median); 4.38 ms (minimum)
Throughput	220.12 images/s
Memory requirements
Largest activation tensor	128.0 MB
Sum of all activations (upper bound)	2,320.2 MB (≈2.3 GB)
Process peak resident memory	≈1.36 GB
Peak GPU memory (batch 16)	4,932.6 MB (≈4.93 GB)