By using SSD, we only need to take one single shot to detect multiple objects within the image, while regional proposal network (RPN) based approaches such as R-CNN series that need two shots, one for generating region proposals, one for detecting the object of each proposal. Thus, SSD is much faster compared with two-shot RPN-based approaches.

Robot-Deployment Team Final Project: Trained Neural Network implementation for custom image recognition

Caffe implementation by @weiliu89 , after training mobilenet ssd v1 based on Caffe

Object detection with machine learning and OpenCV

My playground of self-driving GoPiGo3 car using deep learning for computer vision. Technical details can be found in https://blog.zhijiahu.dev/

MobileNet SSD with Caffe implementation for person detection algorithm.

Classifier | TensorFlow.js | MobileNet

To develop a prototype device for visually-impaired individuals so they can navigate their route through a known or unknown environment by providing data and cues of common objects or of a known person, that surrounds such individual in their day-to-day life, by making a stand-alone device requiring minimum and transportable equipment.

Machine Learning and AI Mobile Application

Python Script to detect Person in your empty apartment and Shoot you an email with the picture Every few Sec

Real time mobile video object detection using MobileNet-SSD trained on KITTI dataset in Tensorflow

Python script for object detection using Intel Movidius Neural Compute Stick and a pretrained model to be further used on Raspberry-based hexapod robot.

Detecting licence plates using OpenALPR Library and finding the people without helmets using helmet detection program

A web application which translates speech to sign language and sign language to speech in order to minimize the communication gap between normal people and the people with special need.

Object detection is detecting and recognizing the object. It is one of the common applications in computer vision problems (like traffic signals, people tracking, vehicle detection, etc...). In this repo, I develop real-time object detection with pre-trained models. These are YOLO version 3 and SSD MobileNet version 3. And I used coco large data…

Covid-19 medical mask detection for public places

ODIN-AI or Object detection and identification ai is a flutter based mobile application that can detect up-to 9 objects in the camera and assign them with their predicted labels. The deep learning technique used is transfer learning using OpenCV and the SSD MobileNet model.

Object detection using MobileNet SSD (D/L)

Real Time Object Detection With MobileNet and SSD