Python still leads despite a dip; C edges past C++ for #2; SQL re-enters the top 10 as Perl drops out after last month’s ...
Abstract: Detecting small, oriented objects in remote sensing images remains a bottleneck for prevailing detection paradigms. The discriminative cues essential for detecting small instances are often ...
Abstract: Object-oriented radio frequency identification (RFID) with machine learning (ML) and the internet of things (IoT) can be used to predict demand for products and services. RFID is a ...
Abstract: Semi-supervised object detection (SSOD), leveraging unlabeled data to boost object detectors, has become a hot topic recently. However, existing SSOD approaches mainly focus on horizontal ...
Abstract: Oriented object detection in aerial images has made significant advancements propelled by well-developed detection frameworks and diverse representation approaches to oriented bounding boxes ...
Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria Vienna Doctoral School in Chemistry (DoSChem), University of Vienna, Währinger ...
Abstract: The detection and recognition of oriented objects in remote sensing images is a challenging task due to their complex backgrounds, various sizes, diverse aspect ratios, and especially ...
#OctopusEffects, #aftereffects Here is a short video on how to remove unwanted objects in your video, using Content-Aware Fill. Removing unwanted objects in a video can be a complicated and time ...
Abstract: Oriented object detection (OOD) in remote sensing images (RSIs) remains a challenging work due to an arbitrary orientation of instances. Learning rotation-invariant features is critical in ...
Abstract: Oriented object detection in remote sensing images (RSIs) relies heavily on costly annotated data. To alleviate this challenge, we propose a straightforward yet powerful approach for ...
Abstract: Oriented object detection in synthetic aperture radar (SAR) images presents significant challenges due to the scarcity of labeled data. In contrast, acquiring labeled optical remote sensing ...
Abstract: Single point-supervised object detection is gaining attention due to its cost-effectiveness. However, existing approaches focus on generating horizontal bounding boxes (HBBs) while ignoring ...
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