arXiv:1812.03451v2 [cs.CV] 8 Jan 2019
Import ONNX* MobileNet v2 Tutorial — OpenVINO™ documentation — Version(2021.4)
GitHub - shicai/MobileNet-Caffe: Caffe Implementation of Google's MobileNets (v1 and v2)
New mobile neural network architectures
Import ONNX* MobileNet v2 Tutorial - OpenVINO™ Toolkit
利用自己的数据集训练MobileNetSSD建立模型，并基于caffe-ssd实现- 知乎
GitHub - FreeApe/VGG-or-MobileNet-SSD: Caffe implementation of Google VGG/ MobileNet/ShuffleNet SSD detection network. Ref: (https://github.com/chuanqi305/MobileNet-SSD) (https://github.com/weiliu89/ caffe) SSD QQ交流群：581437405
SSD Object Detection in Real Time (Deep Learning and Caffe) | by Amolik Vivian Paul | ACM JUIT | Medium
arXiv:1801.04381v4 [cs.CV] 21 Mar 2019
Real-Time Vehicle Detection with MobileNet SSD and Xailient - Edge AI and Vision Alliance
MobileNet-SSD~ssdkerasのその先２~ - Qiita
Rapidly Implement Edge AI Applications with FPGAs | DigiKey
GitHub - maym86/caffe-ssd: Build of caffe with mobilenet SSD - fork of https://github.com/weiliu89/caffe/tree/ssd
Sensors | Free Full-Text | Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse | HTML
深度学习实现目标实时检测Mobilenet-ssd caffe实现_xiao__run的博客-CSDN博客
Real-Time Vehicle Detection with MobileNet SSD and Xailient - Edge AI and Vision Alliance
Real-Time Object Detection on Raspberry Pi Using OpenCV DNN | by Saumya Shovan Roy (Deep) | Heartbeat
GitHub - zhanghanbin3159/MobileNetV2-SSD
GitHub - FreeApe/VGG-or-MobileNet-SSD: Caffe implementation of Google VGG/ MobileNet/ShuffleNet SSD detection network. Ref: (https://github.com/chuanqi305/MobileNet-SSD) (https://github.com/weiliu89/ caffe) SSD QQ交流群：581437405
How to retrain SSD Mobilenet for real-time object detection using a Raspberry Pi and Movidius Neural Compute Stick? - Tolotra Samuel
ssd-mobilenet · GitHub Topics · GitHub
Top 10 Sources to Find Computer Vision and AI Models
Regression with Mobilenet-SSD V2 Caffe-ssd model · Issue #694 · Tencent/ncnn · GitHub
Choose FP16, FP32 or int8 for Deep Learning Models
