mlsanityData to 14 Oct 2026

Squeezed Edge YOLO: Onboard Object Detection on Edge Devices

arXiv 2312.11716 ↗First posted 18 Dec 2023cs.CVcited by 8

Not on the map. Why?

Abstract (arXiv)

Demand for efficient onboard object detection is increasing due to its key role in autonomous navigation. However, deploying object detection models such as YOLO on resource constrained edge devices is challenging due to the high computational requirements of such models. In this paper, an compressed object detection model named Squeezed Edge YOLO is examined. This model is compressed and optimized to kilobytes of parameters in order to fit onboard such edge devices. To evaluate Squeezed Edge YOLO, two use cases - human and shape detection - are used to show the model accuracy and performance. Moreover, the model is deployed onboard a GAP8 processor with 8 RISC-V cores and an NVIDIA Jetson Nano with 4GB of memory. Experimental results show Squeezed Edge YOLO model size is optimized by a factor of 8x which leads to 76% improvements in energy efficiency and 3.3x faster throughout.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 12 of its 26 references that are in the map. First posted on arXiv 18 Dec 2023.

Builds on

12 of 26 references.

References · 12

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  3. 2015SSD: Single Shot MultiBox Detectorcited by 3,130
  4. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,162
  5. 2018CrowdHuman: A Benchmark for Detecting Human in a Crowdcited by 284
  6. 2019A Survey of Deep Learning Applications to Autonomous Vehicle Controlcited by 106
  7. 2018YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computerscited by 34
  8. 2018A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Dronescited by 23
  9. 2022Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehiclescited by 22
  10. 2023TinyissimoYOLO: A Quantized, Low-Memory Footprint, TinyML Object Detection Network for Low Power Microcontrollerscited by 18
  11. 2023Bio-inspired Autonomous Exploration Policies with CNN-based Object Detection on Nano-dronescited by 11
  12. 2023ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agentscited by 5

Built on by

Cited by year

Citing papers per year: 2024: 3; 2025: 5.

8 papers.

  1. 2024TinyVQA: Compact Multimodal Deep Neural Network for Visual Question Answering on Resource-Constrained Devicescited by 5
  2. 2025An Efficient Ground-aerial Transportation System for Pest Control Enabled by AI-based Autonomous Nano-UAVscited by 4
  3. 2025MedMambaLite: Hardware-Aware Mamba for Medical Image Classificationcited by 4
  4. 2024A Deep Learning-based Pest Insect Monitoring System for Ultra-low Power Pocket-sized Dronescited by 3
  5. 2025MambaLiteSR: Image Super-Resolution with Low-Rank Mamba using Knowledge Distillationcited by 3
  6. 2025EdgeNavMamba: Mamba Optimized Object Detection for Energy Efficient Edge Devicescited by 2
  7. 2024Energy-Aware FPGA Implementation of Spiking Neural Network with LIF Neuronscited by 1
  8. 2025Hardware-Aware YOLO Compression for Low-Power Edge AI on STM32U5 for Weeds Detection in Digital Agriculturecited by 1