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Found 6 papers, 3 papers with code
AlphaChimp: Tracking and Behavior Recognition of Chimpanzees
Understanding non-human primate behavior is crucial for improving animal welfare, modeling social behavior, and gaining insights into both distinctly human and shared behaviors.
Reliable edge machine learning hardware for scientific applications
Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing.
ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors
ChimpACT is both comprehensive and challenging, consisting of 163 videos with a cumulative 160, 500 frames, each richly annotated with detection, identification, pose estimation, and fine-grained spatiotemporal behavior labels.
Tailor: Altering Skip Connections for Resource-Efficient Inference
We argue that while a network's skip connections are needed for the network to learn, they can later be removed or shortened to provide a more hardware efficient implementation with minimal to no accuracy loss.
Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark
We present our development experience and recent results for the MLPerf Tiny Inference Benchmark on field-programmable gate array (FPGA) platforms.
Applications and Techniques for Fast Machine Learning in Science
In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time experimental data processing loop to accelerate scientific discovery.
