Abstract: In recent years, optical remote sensing image salient object detection (ORSI-SOD) has made substantial progress. Nevertheless, it remains an open-ended research area with complex challenges.

Abstract: Accurate detection and segmentation of underwater objects in side-scan sonar (SSS) imagery remain challenging due to noise, cluttered backgrounds, and low-contrast conditions. In this paper, ...

Abstract: Large data volumes, dynamic scenes, and intricate object motions make video analysis extremely difficult. Traditional methods depend on human-crafted features that are not scalable. This ...

Abstract: Single-domain generalized object detection aims to enhance a model’s generalization to multiple unseen target domains using only data from a single source domain during training. This is 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: 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 ...

Abstract: Modern diffusion-based image generative models have made significant progress and become promising to enrich training data for the object detection task. However, the generation quality and ...

Abstract: Small object detection in uncrewed aerial vehicle (UAV) images is one of the critical aspects for its widespread application. However, due to limited feature extraction for small objects and ...

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: In the field of remote sensing image processing, remote sensing image object detection is a crucial undertaking. However, the existing object detection algorithms have a considerable number ...