Zobrazeno 1 - 10
of 16 034
pro vyhledávání: '"Abdu, A"'
We investigate the spatiotemporal dynamics of traffic accidents in Addis Ababa, Ethiopia, using 2016--2019 data. We formulate the traffic accident intensity as a log-Gaussian Cox Process and model it as a spatiotemporal point process with and without
Externí odkaz:
http://arxiv.org/abs/2408.02612
This study introduces an approach to optimize Parameter Efficient Fine Tuning (PEFT) for Pretrained Language Models (PLMs) by implementing a Shared Low Rank Adaptation (ShareLoRA). By strategically deploying ShareLoRA across different layers and adap
Externí odkaz:
http://arxiv.org/abs/2406.10785
Emerging discussions on the responsible government use of algorithmic technologies propose transparency and public participation as key mechanisms for preserving accountability and trust. But in practice, the adoption and use of any technology shifts
Externí odkaz:
http://arxiv.org/abs/2405.19187
Low Earth Orbit (LEO) satellite networks are rapidly gaining traction today. Although several real-world deployments exist, our preliminary analysis of LEO topology performance with the soon-to-be operational Inter-Satellite Links (ISLs) reveals seve
Externí odkaz:
http://arxiv.org/abs/2402.08988
Autor:
Yunusa, Haruna, Qin, Shiyin, Chukkol, Abdulrahman Hamman Adama, Yusuf, Abdulganiyu Abdu, Bello, Isah, Lawan, Adamu
The hybrid of Convolutional Neural Network (CNN) and Vision Transformers (ViT) architectures has emerged as a groundbreaking approach, pushing the boundaries of computer vision (CV). This comprehensive review provides a thorough examination of the li
Externí odkaz:
http://arxiv.org/abs/2402.02941
Autor:
Agrawal, Kapil, Jyothi, Sangeetha Abdu
Cloud resilience is crucial for cloud operators and the myriad of applications that rely on the cloud. Today, we lack a mechanism that allows cloud operators to gracefully degrade application performance in public clouds. In this paper, we put forwar
Externí odkaz:
http://arxiv.org/abs/2312.12809
Deploying Large Language Models (LLMs) locally on mobile devices presents a significant challenge due to their extensive memory requirements. In this paper, we introduce LinguaLinked, a system for decentralized, distributed LLM inference on mobile de
Externí odkaz:
http://arxiv.org/abs/2312.00388
Autor:
Mia, Md Sohag, Voban, Abdullah Al Bary, Arnob, Abu Bakor Hayat, Naim, Abdu, Ahmed, Md Kawsar, Islam, Md Shariful
Publikováno v:
International Conference on the Cognitive Computing and Complex Data (ICCD) 2023
Efficient and accurate detection of small objects in manufacturing settings, such as defects and cracks, is crucial for ensuring product quality and safety. To address this issue, we proposed a comprehensive strategy by synergizing Faster R-CNN with
Externí odkaz:
http://arxiv.org/abs/2310.05768
Autor:
Mia, Md Sohag, Arnob, Abu Bakor Hayat, Naim, Abdu, Voban, Abdullah Al Bary, Islam, Md Shariful
Publikováno v:
International Conference on the Cognitive Computing and Complex Data (ICCD) 2023
Transformer design is the de facto standard for natural language processing tasks. The success of the transformer design in natural language processing has lately piqued the interest of researchers in the domain of computer vision. When compared to C
Externí odkaz:
http://arxiv.org/abs/2310.05664
Among the recent advances and innovations in satellite communications, Non-Geostationary Orbit (NGSO) satellite constellations are gaining popularity as a viable option for providing widespread broadband internet access and backhauling services. Howe
Externí odkaz:
http://arxiv.org/abs/2309.10581