Data for: Hydrophobicity Classification of Composite Insulators Based on Convolutional Neural Networks

By applying the spray method (IEC Standard 62073), about 4500 photos were collected and are available online, from all hydrophobicity classes using distilled water-ethyl alcohol as spraying solution. The pictures of the seven different hydrophobicity classes were split into three separate sets for each hydrophobicity class. The first one consisting of 400 instances of each class (400 × 7 = 2800 photos) was used for the training of the networks. The second one consisting of 100 instances of each class (100 × 7 = 700 photos) was used for the evaluation-validation of the learning course and the comparison of the different models. The last one with 122-165 different instances of each class (980 photos) was used for the final assessment of our chosen model.本数据集采用符合IEC 62073标准的喷雾法，以蒸馏水-乙醇混合液作为喷雾溶液，覆盖全部7个疏水性等级（hydrophobicity classes），共采集约4500张可在线获取的照片。针对7种不同的疏水性等级，每个等级的对应照片均被拆分为三个独立数据集：第一子集包含每个等级的400张样本（总计7×400=2800张照片），用于神经网络训练；第二子集包含每个等级的100张样本（总计7×100=700张照片），用于模型学习过程的评估验证以及不同模型的性能对比；第三子集包含每个等级的122至165张样本（总计980张照片），用于对所选模型开展最终性能评估。