Delve into the cutting edge of Artificial Intelligence with our dedicated Research Paper section.
![[2401.02960] Forensic Video Analytic Software](http://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png "[2401.02960] Forensic Video Analytic Software"){kind=logo}
[Submitted on 17 Sep 2023] Download a PDF of the paper titled Forensic Video Analytic Software, by Anton Jeran Ratnarajah and 4 other authors Download PDF Abstract:Law enforcement officials heavily depend on Forensic Video Analytic (FVA) Software in their evidence…
In recent studies, the focus has been on enhancing knowledge graph embedding learning, which encodes entities and relations in knowledge graphs into low-dimensional vector spaces. While current models mainly consider the structural aspects of these graphs, there’s a wealth of…
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Learning an Explicit Hyper-parameter Prediction Function Conditioned on Tasks Jun Shu, Deyu Meng, Zongben Xu; 24(186):1−74, 2023. Abstract Meta learning has attracted much attention recently in machine learning community. Contrary to conventional machine learning aiming to learn inherent prediction rules…
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.…
As the global population continues to expand, the demand for natural resources increases. Unfortunately, human activities account for 23% of greenhouse gas emissions. On a positive note, remote sensing technologies have emerged as a valuable tool in managing our environment.…
Video synopsis, summarizing a video to generate a shorter video by exploiting the spatial and temporal redundancies, is important for surveillance and archiving. Existing trajectory-based video synopsis algorithms will not able to work in real time, because of the complexity…
With the development in cognitive science and Large Language Models (LLMs), increasing connections have come to light between these two distinct fields. Building upon these connections, we propose a conjecture suggesting the existence of a duality between LLMs and Tulving’s…
The problem of structured matrix estimation has been studied mostly under strong noise dependence assumptions. This paper considers a general framework of noisy low-rank-plus-sparse matrix recovery, where the noise matrix may come from any joint distribution with arbitrary dependence across…
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels Hao Wang, Rui Gao, Flavio P. Calmon; 24(26):1−43, 2023. Abstract Machine learning models trained by different optimization algorithms under different data distributions can exhibit distinct generalization behaviors. In…
The recent developments in soft computing cannot be complete without noting the contributions of artificial neural machine learning systems that draw inspiration from real cortical tissue or processes that occur in human brain. The universal approximability of such neural systems…
Equipped with sensing, networking, and computing capabilities, Internet of Things (IoT) such as smartphones, wearables, smart speakers, and household robots have been seamlessly weaved into our daily lives. Recent advancements in Generative AI exemplified by GPT, LLaMA, DALL-E, and Stable…