For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and Fundamental Forces from Imperial College London. Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and ...

Scientists from the Institut Langevin in Paris and TU Wien in Vienna have developed a new technique for detecting hidden objects, such as buried treasure or submarines, using complex acoustical ...

Abstract: Object detection has become crucial due to its extensive applications across various industries. However, the data used to train these models is often sensitive and proprietary, raising ...

Introduction: Accurate vehicle analysis from aerial imagery has become increasingly vital for emerging technologies and public service applications such as intelligent traffic management, urban ...

In recent years, underwater object detection (UOD) has become a prominent research area in the computer vision community. However, existing UOD approaches are still vulnerable to underwater ...

Abstract: Deep object detectors suffer from the gradient contribution imbalance during training. In this paper, we point out that such imbalance can be ascribed to the imbalance in example attributes, ...

I tried to run the object detection using tensorflow example on macOS and it did not compile. The compilation errors are because of conflicting usage of conditions in ...