Winograd convolutions cost us 2 mAP and we didn't notice for a month
TL;DR: We turned on Winograd convolution to shave latency off a pedestrian detector running on a Cortex-A53, got a clean 18% speedup, and silently los…
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TL;DR: We turned on Winograd convolution to shave latency off a pedestrian detector running on a Cortex-A53, got a clean 18% speedup, and silently los…
A comprehensive guide covering history, techniques, datasets, algorithms, tools, real-world applications, and final year project ideas for image recon…
The Idea and the Main Engineering Challenges Recently, I released a new offline AI feature for my Android application as a separate module. The entire…
TL;DR: We spent three weeks chasing a 6 mAP regression in an event-camera object detector. The model was fine. The bug was the accumulation window we …
TL;DR: We ran post-training quantisation (PTQ) and quantisation-aware training (QAT) side by side on the same defect-classification model deployed on …
I needed to build a pipeline that takes drone footage of infrastructure (bridges, facades, roads), detects surface defects like cracks and corrosion, …
This is a submission for the Gemma 4 Challenge: Write About Gemma 4 I Replaced My $500 GPU with a $75 Raspberry Pi: How Gemma 4 Makes Computer Vision …