3、需要一种无创、低成本且准确的乳腺癌分级方法来辅助临床决策。 二、让我们一起看一下Cancer-Net BCa-S数据集 Cancer-Net BCa-S是一个基于合成相关扩散成像(CDIs)的深度放射组学数据集,用于预测乳腺癌的SBR分级。包含了252例患者的预处理(T0)病例,这些病例来自美国放射学院影像网络(ACRIN)6698/I-SPY2研究的1...
bigquery_foreach_table.sh - executes a templated command for each table in a given dataset bigquery_foreach_table_all_datasets.sh - executes a templated command for each table in each dataset in the current GCP project bigquery_table_row_count.sh - gets the row count for a given table big...
Dataset<Row> ds = sqlContext.read().format("csv").option("header","true").load("<S3 Location>"); ds.createOrReplaceTempView("<Table Name>"); Dataset<Row> result_ds = sqlContext.sql("<SQL Query Using <Table Name>>"); Explore More Learn more about Argo CD and how to use it to...
基于PaddleSeg2.2,修改dataset、model、train、val等,实现变化检测功能,使用过程与PaddleSeg完全一致,便于快速进行网络训练、推理 基于PaddleCD使用OCR-CD(魔改OCR-Net),在昇腾杯-变化检测赛道复赛排名TOP14,PRCV2021决赛排名TOP7 目前仅实现了OCR-CD、SNUNet、DSAMNet、CDNet,后续会补充模型 ...
CDTier: A Chinese Dataset of Threat Intelligence Entity Relationships, https://github.com/MuYu-z/CDTier/tree/main/data https://deliverypdf.ssrn.com/delivery.php?ID=959114027008106112098100082069064023033092026034079086085107100010054073031119096123116092112092078094051098022026076113095105106107072014116064040089066122087033114085046...
// Encoders for most common types are automatically provided by importing spark.implicits._ val primitiveDS = Seq(1, 2, 3).toDS() primitiveDS.map(_ + 1).collect() // Returns: Array(2, 3, 4) // DataFrames can be converted to a Dataset by providing a class. Mapping will be done...
imgs_per_gpu=2,#每张gpu训练多少张图片 batch_size = gpu_num(训练使用gpu数量) * imgs_per_gpu workers_per_gpu=1, train=dict( type=dataset_type, ann_file=data_root + 'annotations/instances_train2014.json', img_prefix=data_root + 'train2014/', ...
CDataset可以返回三张图像(时段一、时段二以及标签); transforms结合了rs-aug的增强操作,同时可以读取多通道的img、tif、npy等,也能够对三张图像进行处理; models在前向传播中可以一次性读入两种图片,针对遥感变化检测的模型,目前还在扩展中,现有UNet、Fast-SCNN以及SNUNet-CD(刚刚加入kdj豪华午餐)。 gitee:https://...
The Remote Sensing Image Captioning Dataset (RSICD) is a dataset for remote sensing image captioning task. It contains more than ten thousands remote sensing images which are collected from Google Earth, Baidu Map, MapABC and Tianditu. The images are fix
The dataset is manually collected from Google Earth. It consists of six large bi-temporal high resolution images covering six cities (i.e., Beijing, Chengdu, Shenzhen, Chongqing, Wuhan, Xian) in China. The five large image-pairs (i.e., Beijing, Chengdu,