This paper presents the Multi-Scale Attention Residual Network (MSAR-Net) tailored for multi-organ segmentation tasks within minimally invasive surgical contexts. Central to the MSAR-Net architecture is the integration of the Attention Residual (AR) module.

2024年1月8日 · 高分三号 （GF-3）卫星作为我国第一颗民用多极化C波段SAR卫星，具有分辨率高（可达1米）、成像幅宽大以及成像模式多样的特点，可以探测丰富的地物信息，在数据反演、目标解译领域具有突出优势，高分三号卫星及其指标的详细介绍请看文章 (探秘高分三号卫星，探寻全极化SAR数据产品的独特优势)。 高分三号目前在轨3颗星，组网观测，GF-3数据在SAR目标检测、分类与识别等任务中得到了广泛的应用，面向相关应用的开源数据集被陆续提出，推动 …

2023年9月6日 · Multiclass lightweight SAR detection network (MLSDNet) achieves a high mean average precision (mAP) of 92.99% on the newly released multiclass SAR target datasets (MSAR-1.0) with only 1.42 G FLOPs and 928.25 K Params.

2021年11月1日 · The proposed MSAR-Net consists of stack of multi-scale attention residual (MSAR) blocks for feature refinement, and an up and down-sampling projection (UDP) block for edge refinement of the extracted multi-scale features. These blocks are capable of effectively exploiting the multi-scale edge information, without increasing the number of ...

GrokSAR is an open-source toolbox for SAR target detection and recognition. source activate groksar. # heatmap generation dependencies . # other dependencies . Note: make sure you have cd to the root directory of groksar. For SARDet-100K dataset: For SAR-AIRcraft-1.0 dataset: For MSAR dataset: For AIR-SARShip-1.0 dataset:

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attention residual (MSAR) blocks for feature renement, and an up and down-sampling projection (UDP) block for edge renement of the extracted multi-scale features. These blocks are capable of

Extensive experimental results on three SAR image ship target datasets (SSDD, AIR-SARShip-2.0, and HRSID) and a newly released large multiclass target SAR dataset (MSAR-1.0) show that our HRLE-SARDet achieves 98.4%, 79.2%, 92.5%, and 88.4% mean average precision (mAP) with only 1.09 M parameters and 2.5 G floating-point operations (FLOPs) on ...

The Federal Highway Administration (FHWA) required an electronic, secure, and scalable mobile solution to replace the existing paper assessment and inspection reporting processes that support the Emergency Relief (ER) and Emergency Relief for Federally-owned Roads (ERFO) Programs.

OpenAerialMap is an open service to provide access to a commons of openly licensed imagery and map layer services. Download or contribute imagery to the growing commons of openly licensed imagery. Check out the most recent imagery uploaded. The OpenAerialMap Browser provides a simple way to browse and obtain imagery.