Zobrazeno 1 - 10
of 44 248
pro vyhledávání: '"P A, Rashid"'
Publikováno v:
2024 IEEE International Conference on Advanced Telecommunication and Networking Technologies (ATNT)
This paper describes the implementation of a learning-based lane detection algorithm on an Autonomous Mobile Robot. It aims to implement the Ultra Fast Lane Detection algorithm for real-time application on the SEATER P2MC-BRIN prototype using a camer
Externí odkaz:
http://arxiv.org/abs/2411.14873
Training of large-scale text-to-image and image-to-image models requires a huge amount of annotated data. While text-to-image datasets are abundant, data available for instruction-based image-to-image tasks like object addition and removal is limited
Externí odkaz:
http://arxiv.org/abs/2411.13794
We present a novel technique using Fourier series and Laguerre polynomials to represent morphological features of disc galaxies. To demonstrate the utility of this technique, we study the evolution of asymmetry in a sample of disc galaxies drawn from
Externí odkaz:
http://arxiv.org/abs/2411.11972
Autor:
Powell, Lewis, Kuang, Wenjun, Hawkins-Pottier, Gabriel, Jalil, Rashid, Birkbeck, John, Jiang, Ziyi, Kim, Minsoo, Zou, Yichao, Komrakova, Sofiia, Haigh, Sarah, Timokhin, Ivan, Balakrishnan, Geetha, Geim, Andre K., Walet, Niels, Principi, Alessandro, Grigorieva, Irina V.
Unconventional superconductivity, where electron pairing does not involve electron-phonon interactions, is often attributed to magnetic correlations in a material. Well known examples include high-T_c cuprates and uranium-based heavy fermion supercon
Externí odkaz:
http://arxiv.org/abs/2411.09239
As the integration of the Large Language Models (LLMs) into various applications increases, so does their susceptibility to misuse, raising significant security concerns. Numerous jailbreak attacks have been proposed to assess the security defense of
Externí odkaz:
http://arxiv.org/abs/2411.06426
The performance of embodied agents has been shown to improve by increasing model parameters, dataset size, and compute. This has been demonstrated in domains from robotics to video games, when generative learning objectives on offline datasets (pre-t
Externí odkaz:
http://arxiv.org/abs/2411.04434
That datasets that are used in todays research are especially vast in the medical field. Different types of medical images such as X-rays, MRI, CT scan etc. take up large amounts of space. This volume of data introduces challenges like accessing and
Externí odkaz:
http://arxiv.org/abs/2411.01473
Autor:
Gowaikar, Shreeyash, Berard, Hugo, Mushkani, Rashid, Marchand, Emmanuel Beaudry, Ammar, Toumadher, Koseki, Shin
Advancements in AI heavily rely on large-scale datasets meticulously curated and annotated for training. However, concerns persist regarding the transparency and context of data collection methodologies, especially when sourced through crowdsourcing
Externí odkaz:
http://arxiv.org/abs/2411.00956
Symbolic integration is a fundamental problem in mathematics: we consider how machine learning may be used to optimise this task in a Computer Algebra System (CAS). We train transformers that predict whether a particular integration method will be su
Externí odkaz:
http://arxiv.org/abs/2410.23948
Autor:
Rahman, Md Abdur, Barek, Md Abdul, Riad, ABM Kamrul Islam, Rahman, Md Mostafizur, Rashid, Md Bajlur, Ambedkar, Smita, Miaa, Md Raihan, Wu, Fan, Cuzzocrea, Alfredo, Ahamed, Sheikh Iqbal
Although software developers of mHealth apps are responsible for protecting patient data and adhering to strict privacy and security requirements, many of them lack awareness of HIPAA regulations and struggle to distinguish between HIPAA rules catego
Externí odkaz:
http://arxiv.org/abs/2410.20664