Alternatives

Products that do what Dual YOLOv8n UAV Detection on RK3588S at 42 FPS Using NPU does

1RP
R8 Processor▲96
2017 · hasaranga.com
2
YOLO▲175
Real-time object detection
2017
3
ZeroGPU▲309
The compute efficient layer for AI inference
Jun 2026 · zerogpu.ai
4FT
Fine-tune an 8B model on a 4 GB laptop GPU▲139
Aug 2026 · github.com
51T
15FPS to 60FPS, new GPU real-time flow-based method▲112
2020 · youtube.com
6VA
Vector - A High-Level Programming Language for GPU Computing▲142
2013 · zhehaomao.com
7SO
Set of trained deep learning models for computer vision▲127
2016 · github.com
8FP
Floptimal – Preflop ranges reimagined▲135
2021 · floptimal.com
9AA
An AVR based 8-bit Microcomputer▲43
2015 · usebox.net
10AA
Avanor – Avalanche observation platform▲33
2018 · avanor.se
11OO
Offline Object Detection and Tracking on a Raspberry Pi▲106
2018 · medium.com
12ML
Minimal LLM Post-Training Experiments on an 8GB GPU (SFT, DPO, GRPO)▲21
Aug 2026 · github.com
13SV
SpaCy v2 alpha. New 15MB neural model, multi-language NER, training API▲8
2017 · github.com
14IR
I run a vision model on every screenshot, locally, on a 4GB GPU▲36
Jun 2026 · github.com
15VA
Video++, a Real Time Video Processing Framework Using OpenMP4 and C++14▲33
2014 · github.com
16OS
Open source computer vision platform for drones▲13
2015 · percepto.co
17OD
Object Detection in 50ms on a CPU▲6
2019 · medium.com
18FA
Fixstars AIBooster – Accelerate AI Training and Cut GPU Costs▲7
Hi HN, We're excited to introduce Fixstars AIBooster, our new performance engineering tool designed to significantly accelerate AI model training while optimizing GPU utilization. AIBooster provides: Real-time monitoring of GPU, CPU, memory, and power consumption. Clear visibility into performance bottlenecks, helping developers optimize AI workloads. Proven acceleration of AI training processes—users commonly achieve up to 2-3x speed improvements. Significant cost savings by maximizing infrastructure efficiency. It's free to try, requires minimal setup, and integrates seamlessly into your…
2025 · fixstars.com
19BM
bsv – maximum performance data processing▲7
2020 · github.com
20PA
Piku, a Micro-PaaS for ARM and x86▲19
2019 · github.com
21HT
Hypervisor toolkit for low cost dual core Cortex-A9 platform▲22
2011 · l4dev.org
22FR
FusionCore: ROS 2 sensor fusion that outperforms robot_localization▲11
I built sensor fusion for a mobile robot and reached for robot_localization like everyone does. After spending too long fighting navsat_transform, UTM zone boundaries, and YAML covariance tuning, I wrote my own. FusionCore is a 22 state UKF that fuses IMU, wheel encoders, and GPS in ECEF directly (no coordinate projection, no extra node). It estimates IMU bias, adapts its noise covariance automatically from the innovation sequence, and gates outliers with a chi squared test on every sensor. I benchmarked it against robot_localization EKF on 6 sequences from the NCLT public dataset…
Apr 2026 · github.com
23
LEVANI — AI Second Pilot for UAVs▲6
AI Second Pilot for UAVs, built by a veteran
Jul 2026 · ko-fi.com
24MA
Moondream, a small vision language model that runs on 8GB of RAM▲9
I've been working on training this small vision language model for the last month - excited to release the first prototype today! It is based on SigLIP (image encoder), Phi-1.5 (text model) and trained using the LLaVa-1.5 training dataset. It runs reasonably fast on CPU with ~8GB of RAM in full 32-bit precision. There's plenty of room to speed it up and reduce memory consumption by quantizing the model. I posted a video of it running on my M2 Macbook Air (on CPU not MPS, so performance should be comparable on other hardware) on Twitter to demonstrate inference speed:…
2023 · github.com

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