Zobrazeno 1 - 10
of 28 169
pro vyhledávání: '"Talha, A."'
In this project, we provide a deep-learning neural network (DNN) based biophysics model to predict protein properties. The model uses multi-scale and uniform topological and electrostatic features generated with protein structural information and for
Externí odkaz:
http://arxiv.org/abs/2409.03658
Autor:
Chen, Yuhao, He, Jiangpeng, Czarnecki, Chris, Vinod, Gautham, Mahmud, Talha Ibn, Raghavan, Siddeshwar, Ma, Jinge, Mao, Dayou, Nair, Saeejith, Xi, Pengcheng, Wong, Alexander, Delp, Edward, Zhu, Fengqing
Food computing is both important and challenging in computer vision (CV). It significantly contributes to the development of CV algorithms due to its frequent presence in datasets across various applications, ranging from classification and instance
Externí odkaz:
http://arxiv.org/abs/2409.01966
The popularity of Software Defined Networks (SDNs) has grown in recent years, mainly because of their ability to simplify network management and improve network flexibility. However, this also makes them vulnerable to various types of cyber attacks.
Externí odkaz:
http://arxiv.org/abs/2408.17356
Autor:
Bozkus, Talha, Mitra, Urbashi
Q-learning is widely used to optimize wireless networks with unknown system dynamics. Recent advancements include ensemble multi-environment hybrid Q-learning algorithms, which utilize multiple Q-learning algorithms across structurally related but di
Externí odkaz:
http://arxiv.org/abs/2408.16882
The recently introduced structured input-output analysis is a powerful method for capturing nonlinear phenomena associated with incompressible flows, and this paper extends that method to the compressible regime. The proposed method relies upon a ref
Externí odkaz:
http://arxiv.org/abs/2407.14986
Autor:
He, Jiangpeng, Chen, Yuhao, Vinod, Gautham, Mahmud, Talha Ibn, Zhu, Fengqing, Delp, Edward, Wong, Alexander, Xi, Pengcheng, AlMughrabi, Ahmad, Haroon, Umair, Marques, Ricardo, Radeva, Petia, Tang, Jiadong, Yang, Dianyi, Gao, Yu, Liang, Zhaoxiang, Jueluo, Yawei, Shi, Chengyu, Wang, Pengyu
The increasing interest in computer vision applications for nutrition and dietary monitoring has led to the development of advanced 3D reconstruction techniques for food items. However, the scarcity of high-quality data and limited collaboration betw
Externí odkaz:
http://arxiv.org/abs/2407.09285
The prevalence of AI-generated imagery has raised concerns about the authenticity of astronomical images, especially with advanced text-to-image models like Stable Diffusion producing highly realistic synthetic samples. Existing detection methods, pr
Externí odkaz:
http://arxiv.org/abs/2407.06817
Existing vision-text contrastive learning models enhance representation transferability and support zero-shot prediction by matching paired image and caption embeddings while pushing unrelated pairs apart. However, astronomical image-label datasets a
Externí odkaz:
http://arxiv.org/abs/2407.07315
Autor:
Liang, Paul Pu, Goindani, Akshay, Chafekar, Talha, Mathur, Leena, Yu, Haofei, Salakhutdinov, Ruslan, Morency, Louis-Philippe
Multimodal foundation models that can holistically process text alongside images, video, audio, and other sensory modalities are increasingly used in a variety of real-world applications. However, it is challenging to characterize and study progress
Externí odkaz:
http://arxiv.org/abs/2407.03418
Personalising an interface to the needs and preferences of a user often incurs additional interaction steps. In this paper, we demonstrate a novel method that enables the personalising of an interface without the need for explicit calibration procedu
Externí odkaz:
http://arxiv.org/abs/2407.02269