Detecting oriented targets in remote sensing images amidst complex and heterogeneous backgrounds remains a formidable challenge in the field of object *** frameworks for oriented detection modules are constrained by i...
详细信息
Detecting oriented targets in remote sensing images amidst complex and heterogeneous backgrounds remains a formidable challenge in the field of object *** frameworks for oriented detection modules are constrained by intrinsic limitations,including excessive computational and memory overheads,discrepancies between predefined anchors and ground truth bounding boxes,intricate training processes,and feature alignment *** overcome these challenges,we present ASL-OOD(Angle-based SIOU Loss for Oriented Object Detection),a novel,efficient,and robust one-stage framework tailored for oriented object *** ASL-OOD framework comprises three core components:the Transformer-based Backbone(TB),the Transformer-based Neck(TN),and the Angle-SIOU(Scylla Intersection over Union)based Decoupled Head(ASDH).By leveraging the Swin Transformer,the TB and TN modules offer several key advantages,such as the capacity to model long-range dependencies,preserve high-resolution feature representations,seamlessly integrate multi-scale features,and enhance parameter *** improvements empower the model to accurately detect objects across varying *** ASDH module further enhances detection performance by incorporating angle-aware optimization based on SIOU,ensuring precise angular consistency and bounding box *** approach effectively harmonizes shape loss and distance loss during the optimization process,thereby significantly boosting detection *** evaluations and ablation studies on standard benchmark datasets such as DOTA with an mAP(mean Average Precision)of 80.16 percent,HRSC2016 with an mAP of 91.07 percent,MAR20 with an mAP of 85.45 percent,and UAVDT with an mAP of 39.7 percent demonstrate the clear superiority of ASL-OOD over state-of-the-art oriented object detection *** findings underscore the model’s efficacy as an advanced solution for challenging remote sensing object detection tasks.
Temperature sensing on a flexible platform is essential to many healthcare, e-skin, and robotic applications. In this regard, a polymer-based temperature sensor is fabricated where a conductive polymer material i.e. P...
详细信息
To expedite the characteristic mode analysis (CMA) of electromagnetic target structures, this paper combines frequency- and material-independent reactions (FMIR) with characteristic mode analysis using the volume-surf...
详细信息
Energy prices have increased by more than 62% globally on average, while power companies are trying to provide more affordable energy with different options: fixed-rate, slab-based tariffs, and Time-of-Use pricing. Th...
详细信息
Skin cancer is a highly prevalent form of cancer worldwide. The clinical assessment of skin lesions is crucial for evaluating the disease's characteristics. However, this assessment is often hindered by the variab...
详细信息
The microgrid is a potential solution for implementing smart distributed systems. However, controlling a microgrid is still a complex issue, and many proposed solutions are only based on locally measured signals witho...
详细信息
The capacity to generalize to future unseen data stands as one of the utmost crucial attributes of deep neural networks. Sharpness-Aware Minimization (SAM) aims to enhance the generalizability by minimizing worst-case...
详细信息
Microgrid is a promising way to integrate renewable energy. However, if microgrids connect to the grid dispersedly without regulation, it will cause power fluctuation and voltage violation. To manage microgrids in an ...
详细信息
作者：
Alsharif, MaramRawat, Danda B.
Department of Electrical Engineering & Computer Science WashingtonDC20059 United States
Machine learning based Intrusion detection (ML-IDS) has been long enforced for the protection of the IoT against malicious attacks. Researchers focused on improving ensemble intrusion detection methods in order to boo...
详细信息
暂无评论