Tensorflow Faster RCNN for Object Detection
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Updated
Sep 27, 2021 - Python
Tensorflow Faster RCNN for Object Detection
Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
OpenMMLab Pre-training Toolbox and Benchmark
PaddlePaddle End-to-End Development Toolkit(飞桨低代码开发工具)
Caffe Implementation of Google's MobileNets (v1 and v2)
Implementation of EfficientNet model. Keras and TensorFlow Keras.
Convolutional Neural Networks to predict the aesthetic and technical quality of images.
Creating a software for automatic monitoring in online proctoring
Classification models trained on ImageNet. Keras.
Library for Fast and Flexible Human Pose Estimation
A mobilenet SSD based face detector, powered by tensorflow object detection api, trained by WIDERFACE dataset.
Caffe implementation of SSD and SSDLite detection on MobileNetv2, converted from tensorflow.
A face recognition solution on mobile device.
MobileNetV3 in pytorch and ImageNet pretrained models
High level network definitions with pre-trained weights in TensorFlow
LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)
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