ML Module — Seven classical machine learning classifiers trained on a real-world IoT sensor dataset (62,630 readings, 13 sensor channels) achieve near-perfect AUC-ROC scores above 0.999. DL Module — A ...

Abstract: Space noncooperative object detection (SNCOD) is an essential part of space situation awareness. The localization and segmentation capabilities of the salient object detection (SOD) method ...

ABSTRACT: Effectively detecting subtle surface defects in strip steel is vital for industrial quality assurance; however, most existing approaches fail to strike an optimal balance between accuracy ...

Timely and accurate detection of foreign objects is crucial for the safe operation of transmission lines in power grid. Currently, object detection models have more and more parameters and their ...

Tensorflow Object Detection API is the easy to use framework for creating a custom deep learning model that solves object detection problems. If you already have your own dataset, you can simply ...

ABSTRACT: This paper discusses the task of enhancing malaria detection in thick blood smear images by proposing a UNet-based denoising algorithm. Noise and artifacts in these images can compromise the ...

Astronomers have detected one of the darkest objects ever seen at a record cosmic distance—only with the assistance of gravity. The discovery is an important step toward the observation of dark matter ...

Abstract: This research journal explores the implementation of region-based Convolutional Neural Networks (R-CNN) for precise object detection. Following a systematic six-step approach, it begins by ...