science, including remote sensing, have utilised tremendous improvements in image classification by Convolutional Neural Networks (CNNs) with transfer learning. ... R Naushad,T Kaur,E Ghaderpour 被引量: 0发表: 2021年 加载更多来源期刊 Remote Sensing Letters 研究点推荐 satellite image dataset classif...
Each class has approximately 1300 images. This data was sourced from Kaggle's Satellite Image Classification Dataset. Results Acknowledgments This project was developed as part of the MSCI 446 course, in collaboration with Raynold Yu, Anastan Gnanapragasam, Matthew Stebelsky, and Adriel De Vera....
However, satellite image classification is a challenging problem due to the high variability inherent in satellite data. For this purpose, two learning approaches are proposed and compared for classifying a large-scale dataset including different types of land-use and land-cover surfaces (Eurosat). ...
Satellite imageDeep learningConvolution Neural Networks (CNNs)UC-Merceed Land UseParallel computingNowadays, large amounts of high resolution remote-sensing images are acquired daily. However, the satellite image classification is requested for many applications such as modern city planning, agriculture ...
iSAID: Large-scale Dataset for Object Detection in Aerial Images(IIAI & Wuhan University, Dec 2019) 15 categories from plane to bridge, 188k instances, object instances and segmentation masks (MS COCO format), Google Earth & JL-1 image chips, Faster-RCNN baseline model (MXNet),devkit, Aca...
PASCAL VOC format: XML files in the format used by ImageNet coco-json format: JSON in the format used by the 2015 COCO dataset YOLO Darknet TXT format: contains one text file per image, used by YOLO Tensorflow TFRecord: a proprietary binary file format used by the Tensorflow Object Detect...
This integrated strategy is formulated to enhance classification performance while accommodating the unique demands of an image analysis chain on board OPS-SAT, a nanosatellite operated by the European Space Agency. The experiments performed over a real-world dataset of OPS-SAT images delves into the...
We present the DeepGlobe 2018 Satellite Image Understanding Challenge, which includes three public competitions for segmentation, detection, and classification tasks on satellite images. Similar to other challenges in computer vision domain such as DAVIS and COCO, DeepGlobe proposes three datasets and corre...
iSAID: Large-scale Dataset for Object Detection in Aerial Images(IIAI & Wuhan University, Dec 2019) 15 categories from plane to bridge, 188k instances, object instances and segmentation masks (MS COCO format), Google Earth & JL-1 image chips, Faster-RCNN baseline model (MXNet),devkit, Aca...
Further, the CNN was modeled to obtain the classification of satellite images. Finally, the satellite image classification carried out on the Office-31 dataset and the NWPU-Merced-Land satellite image dataset was performed as follows: Hu et al. [23] presented the Coordinate Partial Adversarial ...