Recognition of Various Objects from a Certain Categorical Set in Real Time Using Deep Convolutional Neural Networks
![Review: MobileNetV1 — Depthwise Separable Convolution (Light Weight Model) | by Sik-Ho Tsang | Towards Data Science Review: MobileNetV1 — Depthwise Separable Convolution (Light Weight Model) | by Sik-Ho Tsang | Towards Data Science](https://miro.medium.com/max/938/1*ylHiMKAXb57bN7uDhzldlg.png)
Review: MobileNetV1 — Depthwise Separable Convolution (Light Weight Model) | by Sik-Ho Tsang | Towards Data Science
![Object detection in office: YOLO vs SSD Mobilenet vs Faster RCNN NAS COCO vs Faster RCNN Open Images - YouTube Object detection in office: YOLO vs SSD Mobilenet vs Faster RCNN NAS COCO vs Faster RCNN Open Images - YouTube](https://i.ytimg.com/vi/llBhBSgoWPs/maxresdefault.jpg)
Object detection in office: YOLO vs SSD Mobilenet vs Faster RCNN NAS COCO vs Faster RCNN Open Images - YouTube
![Review: MobileNetV1 — Depthwise Separable Convolution (Light Weight Model) | by Sik-Ho Tsang | Towards Data Science Review: MobileNetV1 — Depthwise Separable Convolution (Light Weight Model) | by Sik-Ho Tsang | Towards Data Science](https://miro.medium.com/max/1400/1*Voah8cvrs7gnTDf6acRvDw.png)
Review: MobileNetV1 — Depthwise Separable Convolution (Light Weight Model) | by Sik-Ho Tsang | Towards Data Science
![machine learning - SSD MobileNet v1 loss not converging bounding boxes all over the place - Cross Validated machine learning - SSD MobileNet v1 loss not converging bounding boxes all over the place - Cross Validated](https://i.stack.imgur.com/lVZ8a.png)
machine learning - SSD MobileNet v1 loss not converging bounding boxes all over the place - Cross Validated
Capıtulo 4 Resultados Comparación entre SSD y YOLO La tabla 4.7 presenta la comparación de las arquitecturas SSD MobileNet v2
![tensorflow - freeze model for inference with output_node_name for ssd mobilenet v1 coco - Stack Overflow tensorflow - freeze model for inference with output_node_name for ssd mobilenet v1 coco - Stack Overflow](https://user-images.githubusercontent.com/8083613/61330462-3fe5b180-a83d-11e9-99a5-7b63aa1b7d2a.png)