Object detection on dental x-ray images using deep learning method

Using deep learning on X-ray images to detect threats

Detection and Classification of Dental Caries in X-ray Images Using Deep Neural Networks

Dental caries, also known as dental cavities, is the most widespread pathology in the world. Up to a very recent period, almost all individuals had the experience of this pathology at least once in their life. Early detection of dental caries can help in a sharp decrease in the dental disease rate. Thanks to the growing accessibility to medical imaging, the clinical applications now have better...

Oil spill detection using in Sentinel-1 satellite images based on Deep learning concepts

Awareness of the marine area is very important for crisis management in the event of an accident. Oil spills are one of the main threats to the marine and coastal environments and seriously affect the marine ecosystem and cause political and environmental concerns because it seriously affects the fragile marine and coastal ecosystem. The rate of discharge of pollutants and its related effects o...

Object Detection Using Deep CNNs Trained on Synthetic Images

The need for large annotated image datasets for training Convolutional Neural Networks (CNNs) has been a significant impediment for their adoption in computer vision applications. We show that with transfer learning an effective object detector can be trained almost entirely on synthetically rendered datasets. We apply this strategy for detecting packaged food products clustered in refrigerator...

Automatic Road Detection and Extraction From MultiSpectral Images Using a New Hierarchical Object-based Method

Road detection and Extraction is one of the most important issues in photogrammetry, remote sensing and machine vision. A great deal of research has been done in this area based on multispectral images, which are mostly relatively good results. In this paper, a novel automated and hierarchical object-based method for detecting and extracting of roads is proposed. This research is based on the M...