U-Net Model conditioned with MobileNet features for Grayscale -> Color mapping
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Updated
Nov 4, 2017 - Python
U-Net Model conditioned with MobileNet features for Grayscale -> Color mapping
A LEGO-style PyTorch-based Deep Learning Library for ConvNets Modeling
A Artifitial Intelligent Securtiy system that detects humans using a camera and beeps an alarm .
Uses Transfer Learning to create an advanced and more accurate Machine Learning model for classifying type of flowers in the flower dataset
A pre-trained MobileNet model for detecting cracks on concrete structures.
Segmentation with MobileNet
A face recognition solution on mobile device.
What would you say if I told you there is a app on the market that tell you if you have a jackfruit or not a jackfruit.
Implemented the training and inference of several common deep learning model algorithms with tensorflow and pytorch.
Project to handle the Rule of Social Distancing,
Using MobileNetV2 to classify Google's image dataset "cats and dogs".
TensorRT inference (Python and C++) for Chinese single-line and double-line license plate detection and recognition. Optimized for Jetson Nano. 车牌检测,车牌识别,支持单层和双层车牌识别,有 TensorRT Python 和 C++ 的demo, 适合 Jetson Nano 运行。
DiNeSys is a distributed system built for deep learning network profiling on cloud-edge systems, developed with Tensorflow (CNN computational part) Apache Thrift (client/server structure)
A Face Mask Detector created using features from TensorFlow, OpenCV, Keras, and MobileNets on real video streams. This model could be used in real-time applications during the pandemic as well.
Raspberry Pi project using Intel's Neural Compute Stick with pre-trained MobileNet model for edge based streaming inference and SMS notification when class (dog) is in identified in frame
Support project for my Bachelor's thesis @ Unifi - Converting Oxford5k and Paris6k into datasets suitable for object detection tasks. This repository contains scripts to create XML (PASCAL VOC format) and JSON (COCO format) annotations from .pkl files, enabling the training of an SSD/MobileNet object detection model.
Transfer Learning with TensorFlow
Image Models (VGG, ResNet, MobileNet V1, MobileNet V2, Xception Net, DenseNet and more) from scratch.
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