Zobrazeno 1 - 10
of 12 244
pro vyhledávání: '"A. Ansar"'
Autor:
Mahmood, Tariq, Ahmad, Ibtasam, Ansar, Malik Muhammad Zeeshan, Darwish, Jumanah Ahmed, Sherwani, Rehan Ahmad Khan
In recent years, financial analysts have been trying to develop models to predict the movement of a stock price index. The task becomes challenging in vague economic, social, and political situations like in Pakistan. In this study, we employed effic
Externí odkaz:
http://arxiv.org/abs/2409.08297
Autor:
Dawn, Aditya, Ansar, Wazib
Environmental Sound Classification is an important problem of sound recognition and is more complicated than speech recognition problems as environmental sounds are not well structured with respect to time and frequency. Researchers have used various
Externí odkaz:
http://arxiv.org/abs/2408.13644
A language is made up of an infinite/finite number of sentences, which in turn is composed of a number of words. The Electrocardiogram (ECG) is the most popular noninvasive medical tool for studying heart function and diagnosing various irregular car
Externí odkaz:
http://arxiv.org/abs/2407.11102
Autor:
Ansar, Nadia, Ansari, Mohammad Sadique, Sharique, Mohammad, Khatoon, Aamina, Malik, Md Abdul, Siddiqui, Md Munir
There have been significant issues given the IoT, with heterogeneity of billions of devices and with a large amount of data. This paper proposed an innovative design of the Internet of Things (IoT) Environment Intrusion Detection System (or IDS) usin
Externí odkaz:
http://arxiv.org/abs/2406.12400
One of the principal objectives of Natural Language Processing (NLP) is to generate meaningful representations from text. Improving the informativeness of the representations has led to a tremendous rise in the dimensionality and the memory footprint
Externí odkaz:
http://arxiv.org/abs/2406.04438
The advent of transformers with attention mechanisms and associated pre-trained models have revolutionized the field of Natural Language Processing (NLP). However, such models are resource-intensive due to highly complex architecture. This limits the
Externí odkaz:
http://arxiv.org/abs/2406.16893
Available training data for named entity recognition (NER) often contains a significant percentage of incorrect labels for entity types and entity boundaries. Such label noise poses challenges for supervised learning and may significantly deteriorate
Externí odkaz:
http://arxiv.org/abs/2405.07609
Autor:
Ansar, Muhammad Sajjad, Farooq, Bilal
The safe transition from conditional automation to manual driving control is significantly intertwined with the vehicle's lateral and longitudinal dynamics. The transition may occur as a result of a system-initiated mandatory takeover (MTOR) or as a
Externí odkaz:
http://arxiv.org/abs/2402.16046
Autor:
Aynetdinov, Ansar, Akbik, Alan
Instruction-tuned Large Language Models (LLMs) have recently showcased remarkable advancements in their ability to generate fitting responses to natural language instructions. However, many current works rely on manual evaluation to judge the quality
Externí odkaz:
http://arxiv.org/abs/2401.17072
Autor:
Bhaskara, Ramchander, Georgakis, Georgios, Nash, Jeremy, Cameron, Marissa, Bowkett, Joseph, Ansar, Adnan, Majji, Manoranjan, Backes, Paul
Sampling autonomy for icy moon lander missions requires understanding of topographic and photometric properties of the sampling terrain. Unavailability of high resolution visual datasets (either bird-eye view or point-of-view from a lander) is an obs
Externí odkaz:
http://arxiv.org/abs/2401.12414