Zobrazeno 1 - 10
of 50 272
pro vyhledávání: '"Khan, muhammad A."'
Autor:
Cui, Qimei, You, Xiaohu, Wei, Ni, Nan, Guoshun, Zhang, Xuefei, Zhang, Jianhua, Lyu, Xinchen, Ai, Ming, Tao, Xiaofeng, Feng, Zhiyong, Zhang, Ping, Wu, Qingqing, Tao, Meixia, Huang, Yongming, Huang, Chongwen, Liu, Guangyi, Peng, Chenghui, Pan, Zhiwen, Sun, Tao, Niyato, Dusit, Chen, Tao, Khan, Muhammad Khurram, Jamalipour, Abbas, Guizani, Mohsen, Yuen, Chau
With the increasing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and communication for sixth-generation (6G) network is emerging as a revolutionary architecture. This paper presents a
Externí odkaz:
http://arxiv.org/abs/2412.14538
In this study, we consider a real-world application of QML techniques to study water quality in the U20A region in Durban, South Africa. Specifically, we applied the quantum support vector classifier (QSVC) and quantum neural network (QNN), and we sh
Externí odkaz:
http://arxiv.org/abs/2411.18141
Autor:
Akhlaq, Filza, Arshad, Alina, Hayati, Muhammad Yehya, Shamsi, Jawwad A., Khan, Muhammad Burhan
Detecting mixed-critical events through computer vision is challenging due to the need for contextual understanding to assess event criticality accurately. Mixed critical events, such as fires of varying severity or traffic incidents, demand adaptabl
Externí odkaz:
http://arxiv.org/abs/2411.15773
Autor:
Basak, Promit, Sarmun, Rusab, Kabir, Saidul, Al-Hashimi, Israa, Bhuiyan, Enamul Hoque, Hasan, Anwarul, Khan, Muhammad Salman, Chowdhury, Muhammad E. H.
Automated lumbar spine segmentation is very crucial for modern diagnosis systems. In this study, we introduce a novel machine-agnostic approach for segmenting lumbar vertebrae and intervertebral discs from MRI images, employing a cascaded model that
Externí odkaz:
http://arxiv.org/abs/2411.15656
Few-shot segmentation (FSS) aims to segment the target object in a query image using only a small set of support images and masks. Therefore, having strong prior information for the target object using the support set is essential for guiding the ini
Externí odkaz:
http://arxiv.org/abs/2411.11917
Inspired by the success of Geographically Weighted Regression and its accounting for spatial variations, we propose GeogGNN -- A graph neural network model that accounts for geographical latitude and longitudinal points. Using a synthetically generat
Externí odkaz:
http://arxiv.org/abs/2411.04635
Autor:
Khan, Muhammad Tayyab, Chen, Lequn, Ng, Ye Han, Feng, Wenhe, Tan, Nicholas Yew Jin, Moon, Seung Ki
Geometric Dimensioning and Tolerancing (GD&T) plays a critical role in manufacturing by defining acceptable variations in part features to ensure component quality and functionality. However, extracting GD&T information from 2D engineering drawings i
Externí odkaz:
http://arxiv.org/abs/2411.03707
Autor:
Chokuwa, Sharon, Khan, Muhammad Haris
Diabetic Retinopathy (DR) constitutes 5% of global blindness cases. While numerous deep learning approaches have sought to enhance traditional DR grading methods, they often falter when confronted with new out-of-distribution data thereby impeding th
Externí odkaz:
http://arxiv.org/abs/2411.02614
Autor:
Khan, Muhammad Tayyab, Chen, Lequn, Ng, Ye Han, Feng, Wenhe, Tan, Nicholas Yew Jin, Moon, Seung Ki
Automatic feature recognition (AFR) is essential for transforming design knowledge into actionable manufacturing information. Traditional AFR methods, which rely on predefined geometric rules and large datasets, are often time-consuming and lack gene
Externí odkaz:
http://arxiv.org/abs/2411.02810
Many current visual object tracking benchmarks such as OTB100, NfS, UAV123, LaSOT, and GOT-10K, predominantly contain day-time scenarios while the challenges posed by the night-time has been less investigated. It is primarily because of the lack of a
Externí odkaz:
http://arxiv.org/abs/2410.20421