This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic segmentation, and instance segmentation tasks. These datasets are ideal for applications in computer vision, machine learning, remote sensing, and maritime analysis.

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

🔥🔥 🛰️ Official repository of paper on improved two-parameter CFAR algorithm based on Rayleigh distribution and Mathematical Morphology for SAR ship detection. 🔥🔥

This is the official release of LEVIR-Ship, which is a dataset for tiny ship detection under medium-resolution remote sensing images

YOLOv5-ODConvNeXt is an improved version of YOLOv5 for ship detection on drone-captured images.

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

accelerate ship detection with GPU/CUDA SAR Image Processing

[TGRS 2023] An official implementation of Multitype Feature Perception and Refined Network for Spaceborne Infrared Ship Detection

Project on the implementation of deep-learning models for ship detection on SAR images.

Robust CFAR detector based on censored harmonic averaging

Taiwan SAR Ship and Weather Dataset

YOLO-v3 어선 탐지 결과 레퍼지토리

YOLOv8 SAR Ship Detection leverages the YOLOv8 model to detect ships in SAR images and videos. It provides a Streamlit app for real-time detection, displaying bounding boxes around ships with or without confidence scores.

Homeworks for the course Earth Observation Data Analysis, 2020, Sapienza University of Rome

Deep Learning based Ship Detection in Satellite Imagery

Ship detection project developped for Computer Vision exam at UNIVPM

TIPE MPSI/MP* 2018-2020