Zobrazeno 1 - 10
of 5 402
pro vyhledávání: '"A. Fiaz"'
Automated waste recycling aims to efficiently separate the recyclable objects from the waste by employing vision-based systems. However, the presence of varying shaped objects having different material types makes it a challenging problem, especially
Externí odkaz:
http://arxiv.org/abs/2410.24139
Autor:
Kareem, Daniya Najiha Abdul, Fiaz, Mustansar, Novershtern, Noa, Hanna, Jacob, Cholakkal, Hisham
Volumetric medical image segmentation is a fundamental problem in medical image analysis where the objective is to accurately classify a given 3D volumetric medical image with voxel-level precision. In this work, we propose a novel hierarchical encod
Externí odkaz:
http://arxiv.org/abs/2410.15360
Autor:
Paul, Lennart, Urrea-Quintero, Jorge-Humberto, Fiaz, Umer, Hussein, Ali, Yaghi, Hazem, Wessels, Henning, Römer, Ulrich, Stahlmann, Joachim
This work introduces a surrogate modeling approach for an emplacement drift of a deep geological repository based on Gaussian Processes (GPs). The surrogate model is used as a substitute for the high-fidelity mechanical model in many-query scenarios,
Externí odkaz:
http://arxiv.org/abs/2409.02576
Autor:
Khan, Asifullah, Sohail, Anabia, Fiaz, Mustansar, Hassan, Mehdi, Afridi, Tariq Habib, Marwat, Sibghat Ullah, Munir, Farzeen, Ali, Safdar, Naseem, Hannan, Zaheer, Muhammad Zaigham, Ali, Kamran, Sultana, Tangina, Tanoli, Ziaurrehman, Akhter, Naeem
Deep supervised learning models require high volume of labeled data to attain sufficiently good results. Although, the practice of gathering and annotating such big data is costly and laborious. Recently, the application of self supervised learning (
Externí odkaz:
http://arxiv.org/abs/2408.17059
Existing deep learning approaches leave out the semantic cues that are crucial in semantic segmentation present in complex scenarios including cluttered backgrounds and translucent objects, etc. To handle these challenges, we propose a feature amplif
Externí odkaz:
http://arxiv.org/abs/2407.09379
Accurate segmentation of medical images is crucial for diagnostic purposes, including cell segmentation, tumor identification, and organ localization. Traditional convolutional neural network (CNN)-based approaches struggled to achieve precise segmen
Externí odkaz:
http://arxiv.org/abs/2406.17471
Large Language Models (LLMs) pre-trained on multilingual data have revolutionized natural language processing research, by transitioning from languages and task specific model pipelines to a single model adapted on a variety of tasks. However majorit
Externí odkaz:
http://arxiv.org/abs/2405.15453
Change detection (CD) is a fundamental task in remote sensing (RS) which aims to detect the semantic changes between the same geographical regions at different time stamps. Existing convolutional neural networks (CNNs) based approaches often struggle
Externí odkaz:
http://arxiv.org/abs/2404.17565
Autor:
Hill, Spencer A, Meyers, Destiny Zamir, Sobel, Adam H, Biasutti, Michela, Cane, Mark A, Tippett, Michael K, Ahmed, Fiaz
Extreme rainfall in the Indian summer monsoon can be destructive and deadly. Although El Ni\~no/ events in the equatorial Pacific make dry days and whole summers more likely throughout India, their influence on daily extremes is not well established.
Externí odkaz:
http://arxiv.org/abs/2404.12419
Deep learning has shown remarkable success in remote sensing change detection (CD), aiming to identify semantic change regions between co-registered satellite image pairs acquired at distinct time stamps. However, existing convolutional neural networ
Externí odkaz:
http://arxiv.org/abs/2403.17909