SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
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Updated
Nov 11, 2023 - Python
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
A Keras port of Single Shot MultiBox Detector
Computer vision based vehicle detection and tracking using Tensorflow Object Detection API and Kalman-filtering
State-of-the-art Single Shot MultiBox Detector in Pure TensorFlow, QQ Group: 758790869
A Light CNN based Method for Hand Detection and Orientation Estimation
Optical character recognition for Chinese subtitles using SSD and CNN
PyTorch implementation of Grouped SSD (GSSD) and GSSD++ for focal liver lesion detection from multi-phase CT images (MICCAI 2018, IEEE TETCI 2021)
Emotion classification has always been a very challenging task in Computer Vision. Using the SSD object detection algorithm to extract the face in an image and using the FER 2013 released by Kaggle, this project couples a deep learning based face detector and an emotion classification DNN to classify the six/seven basic human emotions.
Single Shot MultiBox Detector implemented with TensorFlow
Cone detector trained using the Tensorflow Object Detection API
PyTorch based implementation of Single Shot Multibox Detector paper
A flask based web app which uses Single Shot Multibox Detector to detect human faces
Single Shot MultiBox Detector deployed on a OAK-D Lite cam via DepthAI
Polyp Localization In Colonscopy Videos using Single Shot Multibox Detector
Single shot multi box detector in Pytorch
Detect Masks on Face
Implements a Single Shot MultiBox Detector to detect products in shelf images. - https://arxiv.org/abs/1512.02325
En el presente repositorio se encuentra el proceso de desarrollo, en fase de prueba de concepto, de un sistema de monitoreo de rapidez y obtención de matrículas de automóviles, dicho proceso se detalla en forma secuencial. Adicional se incluyen los documentos durante el desarrollo y los enlaces a las herramientas necesarias para la elaboración d…
AI-driven weapon detection system for real-time surveillance. Developed on TensorFlow, achieved precision of 0.8524 and 0.7006 at IoU 0.50 and 0.75. Utilizes key frame extraction and SSD-MobileNet, enhancing efficiency. Developed on Windows 10, Python 3.7.3, and TensorFlow 1.14.0. Boosts security with low-cost, automated threat recognition.
Single shot multi box detector in Pytorch
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