Neural networks and related deep learning methods are currently at the leading edge of technologies used for classifying complex objects such as seismograms. However they generally demand large ...

Abstract: We have constructed an algorithm that is able to classify generic sonar objects as divers or not divers. This process was made difficult by the fact that human divers produce amorphous blobs ...

Abstract: In current research one of the main challenges in short range synthetic aperture radar (SAR) is electrically small structures and objects, which tend to unclear reinforced or through the ...

Traditional spectroscopic observations, while precise, are time-consuming and resource-intensive. On the other hand, photometric imaging is more efficient but can lead to ambiguities when classifying ...

“Accurate and rapid identification and depiction of objects from digital images (e.g., aerial images, smartphone images, etc.) and video data is increasingly important for a variety of applications.

The CIFAR10 dataset contains 50,000 training images and 10,000 test images, divided into 10 classes (airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck). Each image is a ...