A project task from Suhora (Space Analytics) company

The official implementation of DRENet (Degraded Reconstruction Enhancement Network) for tiny ship detection in remote sensing Images

Ship detection in Sentinel 1 Synthetic Aperture Radar (SAR) imagery

Ship Detection in SAR Images: A repository for analyzing, training, and testing ship detection models using Synthetic Aperture Radar (SAR) images.

A Cross-Spatial Multi-Scale Lightweight Network for Ship Detection of SAR Images in Complex Scenes

This is a Large-Scale SAR Ship Detection Dataset-v1.0 (LS-SSDD-v1.0) from Sentinel-1, for small ship detec-tion under large-scale backgrounds. LS-SSDD-v1.0 contains 15 large-scale SAR images whose …

Small Vessel Detection from Synthetic Aperture Radar (SAR) Imagery using Deep Learning

Ship Detection using Deep Learning and Machine Learning techniques

An efficient SAR ship detection method

Different Faster R-CNN models implemented to solve sar ship detection

A Novel CNN-based Method for Accurate Ship Detection in HR Optical Remote Sensing Images via Rotated Bounding Box

Matterport's Mask R-CNN library (Added Ship Detection sample) for object detection and instance segmentation on Keras and TensorFlow

[ISBI'20] The Code of “CTF-Net: Retinal vessel segmentation via Deep coarse-to-fine supervision network”

Detecting ships from the satellite images using the YOLO algorithm

Ship Detection from SAR Images

Maritime vessel detection from remote sensing SAR data, based on the architectures of the Faster-RCNN and YOLOv5 networks.

Automatic ship detection with ESA Sentinel-1 SAR imagey.

A toolbox for near-field THz imaging simulation and image reconstruction.

Denoising images with a Deep Convolutional Autoencoder - Implemented in Keras

A selection of functions for working with SAR data.

An implementation of the paper SAR Image Despeckling Using a Convolutional Neural Network by Puyang Wang,