Abstract: Small uncrewed autonmous vehicles (UAVs) equipped with deep learning models are increasingly used to detect small objects both on the ground and in aerial environments. Since small objects ...
Abstract: Camouflaged object detection (COD) is a challenging task that struggles to accurately detect the objects concealed in the surrounding environment. This is largely attributed to the intrinsic ...
Millimeter-wave radar object detection has become pivotal for autonomous driving systems requiring all-weather reliability. While conventional CFAR methods face limitations in classification ...
Abstract: Object detection is a critical task in computer vision, with applications ranging from autonomous driving to medical imaging. Traditional object detection models, such as Fast R-CNN, have ...
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: To address the problems of relying on electronic repositories and being vulnerable to network influence in obtaining key information of literature in mainstream literature management ...
TikTok wants users to believe that errors blocking uploads of anti-ICE videos or direct messages mentioning Jeffrey Epstein are due to technical errors—not the platform shifting to censor content ...
Abstract: Small object detection (SOD) constitutes a notable yet immensely arduous task, stemming from the restricted informative regions inherent in size-limited instances, which further sparks off ...
Abstract: Existing active learning methods for object detection face challenges, such as the lack of ground truth labels for regression loss, insufficient representation of unlabeled instance samples ...
Description 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 ...
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