Zobrazeno 1 - 10
of 37 547
pro vyhledávání: '"Anjum, A. A."'
Autor:
Mohseni, Masoud, Scherer, Artur, Johnson, K. Grace, Wertheim, Oded, Otten, Matthew, Aadit, Navid Anjum, Bresniker, Kirk M., Camsari, Kerem Y., Chapman, Barbara, Chatterjee, Soumitra, Dagnew, Gebremedhin A., Esposito, Aniello, Fahim, Farah, Fiorentino, Marco, Khalid, Abdullah, Kong, Xiangzhou, Kulchytskyy, Bohdan, Li, Ruoyu, Lott, P. Aaron, Markov, Igor L., McDermott, Robert F., Pedretti, Giacomo, Gajjar, Archit, Silva, Allyson, Sorebo, John, Spentzouris, Panagiotis, Steiner, Ziv, Torosov, Boyan, Venturelli, Davide, Visser, Robert J., Webb, Zak, Zhan, Xin, Cohen, Yonatan, Ronagh, Pooya, Ho, Alan, Beausoleil, Raymond G., Martinis, John M.
In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubi
Externí odkaz:
http://arxiv.org/abs/2411.10406
Robotic prostheses and exoskeletons can do wonders compared to their non-robotic counterpart. However, in a cost-soaring world where 1 in every 10 patients has access to normal medical prostheses, access to advanced ones is, unfortunately, extremely
Externí odkaz:
http://arxiv.org/abs/2411.08474
Autor:
Anjum, Md Fahim
Recent advances in image generation, particularly via diffusion models, have led to impressive improvements in image synthesis quality. Despite this, diffusion models are still challenged by model-induced artifacts and limited stability in image fide
Externí odkaz:
http://arxiv.org/abs/2411.09174
Autor:
Morshed, Abrar, Shihab, Abdulla Al, Jahin, Md Abrar, Nahian, Md Jaber Al, Sarker, Md Murad Hossain, Wadud, Md Sharjis Ibne, Uddin, Mohammad Istiaq, Siraji, Muntequa Imtiaz, Anjum, Nafisa, Shristy, Sumiya Rajjab, Rahman, Tanvin, Khatun, Mahmuda, Dewan, Md Rubel, Hossain, Mosaddeq, Sultana, Razia, Chakma, Ripel, Emon, Sonet Barua, Islam, Towhidul, Hussain, Mohammad Arafat
The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings for
Externí odkaz:
http://arxiv.org/abs/2411.05029
Autor:
Anjum, Nafisa, Paul, Alok Kumar
This paper introduces the design and comprehensive characterization of a novel three-layer metamaterial absorber, engineered to exploit the unique optical properties of gold, vanadium dioxide, and silicon dioxide. At the core of this design, silicon
Externí odkaz:
http://arxiv.org/abs/2410.15654
Autor:
Mazumder, Antar, Madhiha, Zarin Anjum
This paper presents L-VITeX, a lightweight visual intuition system for terrain exploration designed for resource-constrained robots and swarms. L-VITeX aims to provide a hint of Regions of Interest (RoIs) without computationally expensive processing.
Externí odkaz:
http://arxiv.org/abs/2410.07872
Autor:
Ovi, Md Sultanul Islam, Anjum, Nafisa, Bithe, Tasmina Haque, Rahman, Md. Mahabubur, Smrity, Mst. Shahnaj Akter
With the increasing adoption of AI-driven tools in software development, large language models (LLMs) have become essential for tasks like code generation, bug fixing, and optimization. Tools like ChatGPT, GitHub Copilot, and Codeium provide valuable
Externí odkaz:
http://arxiv.org/abs/2409.19922
Capitalizing on the intuitive premise that shape characteristics are more robust to perturbations, we bridge adversarial graph learning with the emerging tools from computational topology, namely, persistent homology representations of graphs. We int
Externí odkaz:
http://arxiv.org/abs/2409.14161
Large language models (LLMs) have significantly advanced natural language processing tasks, yet they are susceptible to generating inaccurate or unreliable responses, a phenomenon known as hallucination. In critical domains such as health and medicin
Externí odkaz:
http://arxiv.org/abs/2409.10011
Autor:
Anjum, Md Fahim
In this work, we introduce LightCNN, a minimalist Convolutional Neural Network (CNN) architecture designed for Parkinson's disease (PD) classification using EEG data. LightCNN's strength lies in its simplicity, utilizing just a single convolutional l
Externí odkaz:
http://arxiv.org/abs/2408.10457