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speech-recognition

Hosted files for DEV287x-Speech Recognition Systems

spp_net

SPP_net : Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

srcnn-keras

srcnn-keras-1

srcnn-keras-hdf5

srgan

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

srn

Side-output Residual Network for Object Symmetry Detection in the Wild

srn-deblur

Repository for Scale-recurrent Network for Deep Image Deblurring

ssd-pytorch

SSD目标检测算法(Single Shot MultiBox Detector)(简单,明了,易用,全中文注释,单机多卡训练,视频检测)( If you train the model on a single computer and mutil GPU, this program will be your best choice , easier to use and easier to understand )

ssd-tensorflow

Single Shot MultiBox Detector in TensorFlow

ssd-utils

sssegmentation

SSSegmentation is an open source strongly supervised semantic segmentation toolbox based on PyTorch.

stackalign

Image Alignment Toolbox for Matlab

stat212b

Topics Course on Deep Learning UC Berkeley

steger

An Unbiased Detector of Curvilinear Structures

stereomatching

Some basical stereo matching methods

strokewidthtransform

A playground implementing Epshtein, Ofek, and Wexler's Stroke Width Transform

subpixel

subpixel: A subpixel convnet for super resolution with Tensorflow

subpixel_corner_edge_detector

Subpixel corner and edge detector

subpixel_measurement

Measured the size of the industrial products with sub-pixel accuracy

subpixeledgedetect

An image edge detector is described which produces chained edge points with sub-pixel accuracy.The method incorporates the main ideas of the classic Canny and Devernay algorithms. Theanalysis shows that a slight modification to the original formulation improves the sub-pixelaccuracy of the edge points.

super-resolution.benckmark

Benchmark and resources for single super-resolution algorithms

superresolution

超分辨率SuperResolution

superresolution_caffe

Implementate super resolution in deep learning

surface-defect-detection

缺陷检测文献记录

surface-defect-detection-1

📈 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.

surface-inspection-defect-detection-dataset

This project include several different surfaces, each surface contains one or several defects. For segmentation,object detection, saliency detection，etc

svhn-classification-opencv

SVHN classification using tensorflow model in opencv.

swin-transformer-semantic-segmentation

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.

switchable-normalization

Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10779