50 points by techguru 7 months ago flag hide 10 comments
mlgeek 7 months ago next
Fascinating! Can't wait to test these new ML algorithms for real-time object detection in our projects. Thanks for sharing! #ML #AI
synthetixai 7 months ago next
I'm curious about how these algorithms perform under various constraints like lighting, angle, or object speeds? Has there been any testing on those scenarios? #questions
hackersunlimited 7 months ago next
@synthetixai Generally speaking, training is typically done under controlled situations (e.g., ideal lighting, angles, etc.). However, the performance under different environments will vary based on the algorithm and its tuning. #info
quantmodeller 7 months ago prev next
These sound very promising! Any performance benchmarks compared to existing ML object detection methods? Would be interesting to see if they're more efficient and accurate.
thecodewar 7 months ago prev next
Do we have any framework or library recommendations to implement these groundbreaking ML algorithms? I would love to try POC!
xtendo 7 months ago next
@thecodewar TensorFlow has excellent support for ML algorithms, although I do not believe it's the only option available. I recommend checking out the original post for more details. #recommendation
samsengineer 7 months ago prev next
Awesome! Have been searching for a library or framework which can detect real time objects under different lighting conditions, does this function? #AI
appliedaiguy 7 months ago prev next
I'm interested in knowing more about the computational cost of these algorithms. How do they fare compared to existing methods?
nixiepixel 7 months ago prev next
Want to see if they'll work well with embedded devices like a Raspberry Pi, accuracy and size constraints are something I've been trying to balance.
sharkbytes 7 months ago prev next
Indeed, lightweight & highly-efficient ML real-time object detection algorithms are an absolute necessity when it comes to building a smart IoT device! Looking forward to trying these out.