相关论文: aDORe: a modular, standards-based Digital Object R…
We present DIPO, a novel framework for the controllable generation of articulated 3D objects from a pair of images: one depicting the object in a resting state and the other in an articulated state. Compared to the single-image approach,…
Training deep learning (DL) models on petascale datasets is essential for achieving competitive and state-of-the-art performance in applications such as speech, video analytics, and object recognition. However, existing distributed…
The concept of FAIR Digital Objects represents a foundational step towards realizing machine-actionable, interoperable data infrastructures across scientific and industrial domains. As digital spaces become increasingly heterogeneous,…
FAIR Digital Object (FDO) is an emerging concept that is highlighted by European Open Science Cloud (EOSC) as a potential candidate for building a ecosystem of machine-actionable research outputs. In this work we systematically evaluate FDO…
In order to make results of computational scientific research findable, accessible, interoperable and re-usable, it is necessary to decorate them with standardised metadata. However, there are a number of technical and practical challenges…
Content-centric mobile hybrid Internet-of-Things (IoT) networks consisting of mobile devices and static femto access points (FAPs) are studied, where each device moves according to the random walk mobility model and requests a content…
Substantial efforts have been devoted more recently to presenting various methods for object detection in optical remote sensing images. However, the current survey of datasets and deep learning based methods for object detection in optical…
We propose the Ratio1 AI meta-operating system (meta-OS), a decentralized MLOps protocol that unifies AI model development, deployment, and inference across heterogeneous edge devices. Its key innovation is an integrated blockchain-based…
We propose and evaluate age of information (AoI)-aware multiple access mechanisms for the Internet of Things (IoT) in multi-relay two-hop networks. The network considered comprises end devices (EDs) communicating with a set of relays in…
Aggregations of Web resources are increasingly important in scholarship as it adopts new methods that are data-centric, collaborative, and networked-based. The same notion of aggregations of resources is common to the mashed-up, socially…
More and more emerging Internet of Things (IoT) applications involve status updates, where various IoT devices monitor certain physical processes and report their latest statuses to the relevant information fusion nodes. A new performance…
Recent studies show that using potential out-of-distribution (OOD) labels from large corpora as auxiliary information can improve OOD detection in vision-language models (VLMs). However, these methods often fail when real-world OOD samples…
We present a system for localizing sound sources in a room with several ad-hoc microphone arrays. Each circular array performs direction of arrival (DOA) estimation independently using commercial software. The DOAs are fed to a fusion…
The ability to store multiple versions of a data item is a powerful primitive that has had a wide variety of uses: relational databases, transactional memory, version control systems, to name a few. However, each implementation uses a very…
Out-of-distribution (OOD) object detection is a critical task focused on detecting objects that originate from a data distribution different from that of the training data. In this study, we investigate to what extent state-of-the-art…
Modern NVMe SSDs and RDMA networks provide dramatically higher bandwidth and concurrency. Existing networked storage systems (e.g., NVMe over Fabrics) fail to fully exploit these new devices due to inefficient storage ordering guarantees.…
Endowing robots with the ability to rearrange various large and heavy objects, such as furniture, can substantially alleviate human workload. However, this task is extremely challenging due to the need to interact with diverse objects and…
Access libraries such as ROOT and HDF5 allow users to interact with datasets using high level abstractions, like coordinate systems and associated slicing operations. Unfortunately, the implementations of access libraries are based on…
Hardware and OS mechanisms for memory tiering are widely deployed, yet datacenters still overprovision DRAM. The root cause is hotness fragmentation: allocators place objects by size rather than access pattern, so hot and cold objects…
ASPID stands for the "Archive of Spectral, Photometric, and Interferometric Data". The world largest collection of raw 3D spectroscopic observations of galactic and extragalactic sources is provided. ASPID-SR is a prototype of an archive of…