Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis

Table 5

Brief summary about various layers in CNN architecture.

Layer	Description
Convolutional layer	The primary feature extraction or learning layer, which is made up of various filters and learnable kernels, develops an ideal feature map based on the input data and formulates distinct patterns for each of the data provided as input.
Pooling layer	The layer is layered with the convolutional layer, which is recognised as a downsampling layer since it focuses largely on lowering dimensional complexity.
Fully connected layers	A deep learning algorithm penultimate layer which is in charge of generating vectors of picture matrices. For multiclass issues, fully linked layers with softmax activation functions execute the classification operation (sigmoid activation for binary class problems)