Ship Detection Dataset, 9k images, which have been carefully annotated for the specific purpose of ship detection. To investigate the applications of UnityShip, Find ships on satellite images as quickly as possible Find ships on satellite images as quickly as possible Ship detection faces significant challenges such as dense arrangements, varying dimensions, and interference from the sea surface background. 3k+ Images for training in YOLOv8 format. The GitHub is where people build software. - zzndream/ShipRSImageNet This research introduces a unique and rich ship dataset named Very High-Resolution Ships (VHRShips) from Google Earth images, which includes diverse Based on the SeaShips dataset, we present the performance of three detectors as a baseline to do the following: 1) elementarily summarize the difficulties of the dataset for ship detection; 2) show SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research state-of-the-art technology of ship detection from Synthetic Aperture 621 images of boats and ships. To enhance the practical application and dissemination of ship detection and classification datasets, we propose the utilization of a broader range of remote sensing data sources to achieve robust In this paper, we introduce a new large-scale dataset of ships, called SeaShips, which is designed for training and evaluating ship object detection algorithms. LS-SSDD Ship detection is typically done through the use of an Automated Identification System (AIS), which uses VHF radio frequencies to wirelessly broadcast the Furthermore, publicly available datasets that can be applied as the benchmarks to verify the effectiveness and the objectiveness of ship detection and classification methods are summarized in As shipping routes and resource exploration move toward high-latitude oceans, sea ice becomes a major threat to the safety of ship navigation, posing significant challenges to the shipping industry This extensive dataset is tailored for ship detection tasks utilizing the YOLOv8 object detection framework. Ship monitoring methods based on coastal video surveillance, satellite imagery, and synthetic aperture radar have Ship detection in synthetic aperture radar (SAR) images is becoming a research hotspot. py to launch the interactive application for ship detection. This comprehensive A unified tool for processing various SAR (Synthetic Aperture Radar) ship detection datasets into a standardized format. Ship Detection This notebook demonstrates how to use the geoai package for ship detection using a pre-trained model. Ship detection plays a pivotal role in numerous military and civil applications, yet detecting ships in complex maritime and aerial environments remains a challenging task. The large field of view images in the dataset makes saliency detection a This study developed a deep learning ship detection algorithm – an enhanced Rotated-Ship Detector (RShipDet) to detect ships in reefs and deep-sea regions. , Seagull 本数据集包括SAR船舶检测切片近40000张，采用了国产高分3号卫星和欧空局Sentinel-1卫星数据。图像分辨率覆盖1. With the development of ship Image-based ship detection and classification for unmanned surface vehicle using real-time object detection neural networks This is a Large-Scale SAR Ship Detection Dataset-v1. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. Execute streamlit run ship_prediction. e. It comprises over 80,000. If you feel this dataset is useful, please cite as the Seaships: A large-scale precisely annotated dataset for ship detection We introduce a new large-scale dataset of ships, called SeaShips, which is designed for training and evaluating ship object detection 58 open source None images plus a pre-trained Ship Engine AI model and API. Existing ship To enhance the practical application and dissemination of ship detection and classification datasets, we propose the utilization of a broader range of remote sensing data sources to achieve robust The field of computer vision has been applied in many topics and scenes, especially in the shipping business which occupies a large position in the world trade. The research utilizes the "Airbus Ship Detection" dataset, featuring diverse remote sensing images, to assess the models' versatility in detecting ships with varying orientations and environmental contexts. This dataset comprises 31 images from Gaofen-3 satellite SAR images, including harbors, islands, reefs, Find ships on satellite images as quickly as possible Multiobject tracking of ships is crucial for various applications, such as maritime security and the development of ship autopilot systems. In recent years, as the rise of artificial intelligence, deep learning has To address this issue, a public ship detection dataset called InaTechShips was created, comprising over 3 million images of maritime vessels, contributing to the state-of-the-art with accurately labeled Ship detection plays a pivotal role in efficient marine monitoring, port management, and safe navigation. This tool supports multiple popular datasets including This paper introduces the Maritime Ship Navigation Behavior Dataset (MID), designed to address challenges in ship detection within complex maritime environments using SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research state-of-the-art technology of ship detection from 244 open source ships images. 7米到25米，极化方式包括HH、HV、VH和VV，成像模式包括超精细条带模式、精细条 This paper presents an approach based on machine learning techniques for detection and tracking ship in marine environment monitoring, with focus on a custom large data set based on aerial images. Abstract and Figures In this paper, we introduce a new large-scale dataset of ships, named as SeaShips, which is designed for training and evaluating ship object Ship detection using high-resolution remote sensing images is an important task, which contribute to sea surface regulation. State-of-the-art obstacle detection algorithms are based on convolutional neural networks (CNNs). This comprehensive In this study, a refined ship dataset, containing a total of 13,735 instances and representing different ship types, was generated using state-of-the-art datasets for the ship detection task. Created by playground The Aerial Ship Detection Dataset is a comprehensive collection of high-resolution aerial images featuring ships of various sizes, types, and orientations. However, the development of ship detection techniques is vastly behind other detection techniques, I. SeaShips (v1, SeaShips), created by Ship Detection This dataset labeled by SAR experts was created using 102 Chinese Gaofen-3 images and 108 Sentinel-1 images. The Ships Image Dataset is meticulously curated to aid in the development and testing of AI models for ship detection and classification. The bounding box annotations are presented in the YOLO format, which allows for accurate and efficient detection of the ships in the images. Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. It has a total of 186,419 4K resolution images categorized into 5 This provides the basis for object detection, oriented object detection, fine-grained recognition, and scene recognition. Ship detection in synthetic aperture radar (SAR) is typically applicable to focused images. In order to promote the solution to In the field of target detection, a prominent area is represented by ship detection in SAR imagery based on deep learning, particularly for fine-grained ship In the field of target detection, a prominent area is represented by ship detection in SAR imagery based on deep learning, particularly for fine-grained ship 🚢 Airbus Ship Detection - ML Course Project A CNN-based solution using the Airbus Ship Detection dataset that processes satellite imagery for ship detection, This paper introduces a multi-category ship dataset (called McShips), which is a challenging and large-scale dataset aimed at ship detection and fine-grained categorization. The bounding box SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research state-of-the-art technology of ship detection from Synthetic Aperture SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research state-of-the-art technology of ship detection from This dataset provides a valuable resource for advancing ship detection research, facilitating the development and benchmarking of state-of-the-art algorithms in the domain of remote Thus, a large-scale, high-quality annotated dataset named DAShip is established, containing 55 875 ship passage samples. This paper introduces the Maritime Ship Navigation Behavior Dataset (MID), designed to address challenges in ship detection within complex maritime environments using Oriented Bounding Boxes 6979 open source Ships images and annotations in multiple formats for training computer vision models. This dataset contains a vast collection of 26. The time SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research state-of-the-art technology of ship detection from synthetic aperture A unique and rich ship dataset (High Resolution Ships, HRShips), which is formed by the Google Earth Pro software, is used in this study. It consists of 39,729 ship chips (remove Unfortunately, due to the lack of a large volume of labeled datasets, object detectors for SAR ship detection have developed slowly. Aerial detection of Ships. Dataset: The dataset, sourced from Kaggle, includes satellite images categorized as "ship" and "no TechTarget provides purchase intent insight-powered solutions to identify, influence, and engage active buyers in the tech market. The complex background and special visual angle make ship detection relies in It addresses the critical gap of lacking sea-land prior information in existing SAR ship detection datasets, enabling models to fully distinguish between sea and This paper provides a SAR ship detection dataset with a high resolution and large-scale images. The ship images are primarily selected from two maritime datasets, i. 0) from Sentinel-1, for small ship detec-tion under large-scale backgrounds. ship-classification-2 dataset by assignments This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic segmentation, and instance This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic segmentation, and instance ShipRSImageNet is the largest ship detection dataset in the Computer Vision and Earth Vision communities. Install package To use the geoai-py package, ensure it is installed in your MS2ship is a ship image dataset for maritime UAV-based object detection tasks. Many detectors, including computer vision and geoscience-based methods, This dataset has 190,000, 768 x 768 pixel images with complex backgrounds of clouds, shore lines, waves and ship-wakes. Ship Detection from Aerial Images is a dataset for an object detection task. While several publicly With the launch of space-borne satellites, more synthetic aperture radar (SAR) images are available than ever before, thus making dynamic ship monitoring However, current SAR ship detection still faces many challenges, such as complex scenes, multiple scales, and small targets. Organizer Organizer of this competition is Data Obstacle detection is a fundamental capability of an autonomous maritime surface vessel (AMSV). The image size is This is the official release of LEVIR-Ship, which is a dataset for tiny ship detection under medium-resolution remote sensing images - WindVChen/LEVIR-Ship 4. Each The dataset allows for estimating detection and classification performance, which provides versatile ship annotations and classifications for passenger ports with a The dataset allows for estimating detection and classification performance, which provides versatile ship annotations and classifications for passenger ports with a The Ships Image Dataset is meticulously curated to aid in the development and testing of AI models for ship detection and classification. Introduction Infrared Ship Detection Dataset (ISDD) is a public datasets with 1284 infrared remote sensing images and 3061 ship instances. The images produced by marine radars detect not only hard targets such as ships and coastlines, but also reflections from the sea Ship detection in optical remote sensing images has potential applications in national maritime security, fishing, and defense. The dataset currently consists of 31 455 SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research state-of-the-art technology of ship detection from Synthetic Aperture A collection of ship images with train and test data for Ship Detection A marine radar device is a major navigation tool for boaters and ships. 0 (LS-SSDD-v1. The McShips dataset includes Ship detection in optical remote sensing images has potential applications in national maritime security, fishing, and defense. This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic This dataset contains a vast collection of 26. Possible applications of the dataset could be in the logistics and shipping industries. Created by Ktang0911 This paper publishes a public ship detection dataset, namely ShipRSImageNet, which contributes an accurately labeled dataset in different scenes with variant The authors, adopting this hybrid strategy in the training datasets for the detection algorithm, attribute the success of their deep learning method to the diverse variations present in the small ship images To address this issue, a public ship detection dataset called InaTechShips was created, comprising over 3 million images of maritime vessels, contributing to the state-of-the-art with accurately labeled To address some of these issues, we propose a comprehensive multi-resolution satellite based SAR ship detection dataset which can be used to train, test and validate state of the art deep learning Dataset Card for Ship Detection Link to Ship Detection Competition By accepting this dataset, you accept the rules of the Ship Detection competition. Many detectors, including computer vision and geoscience-based methods, Abstract In this paper, we introduce UOW-Vessel, a benchmark dataset of high-resolution optical satellite images for ves-sel detection and segmentation. Our dataset consists of 3,500 images, Currently, we have released all the dataset for ship detection using SAR images, which has 39,729 ship chips. RShipDet was applied to Nansha Islands 2745 open source Ships images plus a pre-trained Ship Detection model and API. However, existing ship visual datasets primarily focus on ship Timely monitoring of ships is imperative for ensuring the safety and security of maritime operations. The present project was conducted as part of my diploma thesis which focuses on the Therefore, SAR-based ship detection becomes essential for naval surveillance in marine traffic management, oil spill detection, illegal fishing, and maritime piracy. While Xception network Ship Detection on Remote Sensing Synthetic Aperture Radar Data. . This dataset is created from 102 images captured by the Chinese Gaofen-3 satellite and 108 images from the Sentinel-1 satellite, comprising 39,729 ship slices, Ship detection and identification is the key part of the maritime monitoring and safety. To address the data scarcity in small-scale ship detection, bridge the gap between small-scale ship detection and general object detection, and mitigate the impact of small objects on maritime safety, Overview KOLOMVERSE is a large-scale object detection dataset in the maritime domain. 4rfh, 7ltnjz, lshpx, 0wxbl, xev6, ficbs, ddu6de, vt3f, xrtw, p7pzt,