In this article, a novel method for interferometric target detection that employs coherent echoes and spatial frequency sampling is proposed. Originating from radio astronomy, interferometric passive microwave imaging has become widely applied for the passive microwave remote sensing of Earth. The proposed technique, termed Interferometric Coherent Echo Detection, is a novel active imaging method that capitalizes on coherent echoes to sample the spatial frequency domain.

The Asian Subcontinent Dataset (ASCD) is a multisensor dataset that includes geospatial data collected from different countries within the Asian subcontinent, specifically India, Bangladesh, and Sri Lanka. The dataset consists of imagery captured through two main sources: Google Earth Pro software and IKONOS-2 satellite images. ASCD includes 14 distinct land cover classes, ranging from urban areas to natural environments, with 1,674 images. The number of images in each land cover class varies between 100 and 204.

The necessity for strong security measures to fend off cyberattacks has increased due to the growing use of Industrial Internet of Things (IIoT) technologies. This research introduces IoTForge Pro, a comprehensive security testbed designed to generate a diverse and extensive intrusion dataset for IIoT environments. The testbed simulates various IIoT scenarios, incorporating network topologies and communication protocols to create realistic attack vectors and normal traffic patterns.

This dataset is from "One-Stage Cascade Refinement Networks for Infrared Small Target Detection." It includes 427 infrared images and 480 targets (due to the lack of infrared sequences, SIRST also contains infrared images at a wavelength of 950 nm, in addition to shortwave and midwave infrared images). Approximately 90% of the images contain only one target, while about 10% have multiple targets (which may be overlooked in sparse/significant methods due to global unique assumptions).