Deep learning for photovoltaic panels segmentation

An electronic load for testing photovoltaic panels

The characteristics of photovoltaic (PV) panels in the field conditions are to be obtained using a fast varying load. The paper presents a simple electronic load for testing a set of PV panels using linear metal oxide field effect transistors (MOSFETs). The proposed test set up gives the current versus voltage and power versus voltage characteristics of PV panels by quickly scanning the load. D...

Deep Learning for Medical Image Segmentation

This report provides an overview of the current state of the art deep learning architectures and optimisation techniques, and uses the ADNI hippocampus MRI dataset as an example to compare the effectiveness and efficiency of different convolutional architectures on the task of patch-based 3dimensional hippocampal segmentation, which is important in the diagnosis of Alzheimer’s Disease. We found...

Deep Learning for Radiographic Image Segmentation

Despite recent advances, radiographic image segmentation remains a challenging task. This is especially true if the acquired images are degraded by artifact or distracting underlying pathology, conditions under which many state-of-the-art algorithms will fail but which are common in clinical practice. We hypothesize that a deep learning algorithm can be trained for accurate segmentation even in...

Semantic Segmentation with Deep Learning

We present a deep convolutional neural network approach for producing semantic segmentations. First, we generalize the architecture of the successful Alexnet network [7] to directly predict coarse segmentations. Second, we produce full resolution segmentations by re-ranking a diverse set of plausible segmentation proposals generated from a recent state of the art approach [9].

Measured Performance of Building Integrated Photovoltaic Panels