Abstract: Detection transformer (DETR) has emerged as a highly promising approach in object detection (OD) and has attracted significant interest. However, most DETR-like methods cannot simultaneously ...

Abstract: The availability of unprecedented unsupervised training data, along with neural scaling laws, has resulted in an unprecedented surge in model size and compute requirements for ...

Abstract: The upcoming 6G Non-Terrestrial Networks (NTN) technology is expected to enable comprehensive connectivity of the Internet of Things (IoT) across various environments. The presence of a ...

Abstract: Hyperspectral image (HSI) classification has been extensively studied in the context of Earth observation. However, its application in Mars exploration remains limited. Although ...

Abstract: A printed circuit board (PCB) functions as a substrate essential for interconnecting and securing electronic components. Its widespread integration is evident in modern electronic devices, ...

Abstract: Pavement defect detection is of profound significance regarding road safety, so it has been a trending research topic. In the past years, deep learning based methods have turned into a key ...

Abstract: Over the past decade, domain adaptation has become a widely studied branch of transfer learning which aims to improve performance on target domains by leveraging knowledge from the source ...

Abstract: Small-cell mobile edge computing (SE-MEC) networks amalgamate the virtues of MEC and small-cell networks, enhancing data processing capabilities of user devices (UDs). Nevertheless, ...

Abstract: This standard specifies interchange and arithmetic formats and methods for binary and decimal floating-point arithmetic in computer programming environments. This standard specifies ...

Abstract: Recently, three-dimensional (3D) point-cloud analysis has been extensively utilized in the domain of machine vision, encompassing tasks include shape classification and segmentation. However ...

Impact Statement: Understanding the full potentials and limitations of generative AI and LLMs shapes the future of NLP and its impact on various industries and societies. This article explores the ...

Abstract: Multilabel feature selection solves the dimension distress of high-dimensional multilabel data by selecting the optimal subset of features. Noisy and incomplete labels of raw multilabel data ...