Sonar Common Target Detection Dataset . Contribute to MingqiangNing/SCTD development by creating an account on GitHub.
A rapid API for the Project Sonar dataset. Contribute to Cgboal/SonarSearch development by creating an account on GitHub.
Our DNTFE-Net exhibits superior recognition performance on the real sonar dataset compared to other popular methods, with an improvement of at least 27%. Our algorithms are publicly available at https://github.com/zbyhnu/DNTFE-Net.git .Boyu Zhao...
One can access the data from github (https://github.com/violetweir/PPYOLO-T/tree/main/dataset, 2022-08-12). There are 5,000 images in total, of which 4,000 for training and 1,000 for test. Table 1 shows details about object categories and the number of sonar images for each ...
加载数据集样例:sns.load_dataset(<name>,cache=True,data_home=None,**kwargs) #这些数据集样例是Seaborn内置的,每个都有自己的名字;返回pandas.core.frame.DataFrame对象 #参数说明: name:指定数据集;为str #在线数据集文件参见:https://github.com/mwaskom/seaborn-data ...
Our experimental results highlight thatthe S3Simulator dataset will be a promising benchmark datasetfor research on underwater image analysis. https://github.com/bashakamal/S3Simulator . 展开 会议名称: International Conference on Pattern Recognition 会议时间: 2025 ...
The code and dataset are publicly available at https://github.com/Jorwnpay/Sonar-OLTR . 展开 关键词: Sonar image recognition Open-set recognition Long-tail learning DOI: 10.1016/j.eswa.2024.123495 年份: 2024 收藏 引用 批量引用 报错 分享 ...
文章目录? NVIDIA Irregular Mask Dataset: Testing Set(应用最广泛的mask数据)? QD-IMD: Quick Draw Irregular Mask Dataset (较少论文引用)? 两个Mask数据集示例如下? 引用? NVIDIA Irregular Mask test Dataset 快速获取途径如下? 预祝各位 前途似锦、可摘星辰 ? NV MASKRCNN下载 Irregular Mask 图像修复Mask...
The last column in the dataset serves as a crucial indicator, distinguishing whether an object is a mine or a rock, thereby facilitating accurate predictions. You can find the dataset included in this repository. Model The chosen model for this project is Logistic Regression. Logistic regression ...
在通过十次五折交叉验证训练完BETL之后,您会得到y_hat, y_true和logits结果,默认存放在"/output/result/{dataset}/{method}/{backbone}/"路径下,例如,"/output/result/NKSID/jbhtpl/resnet18/y_hat.txt"。然后,您可以使用下面的命令来得到Gmean、Macro-F1、混淆矩阵和P-R曲线结果: ...