Zobrazeno 1 - 10
of 26 692
pro vyhledávání: '"A Ferhat"'
Massive MIMO (Multiple-Input Multiple-Output) is an advanced wireless communication technology, using a large number of antennas to improve the overall performance of the communication system in terms of capacity, spectral, and energy efficiency. The
Externí odkaz:
http://arxiv.org/abs/2501.01802
Autor:
Erata, Ferhat, Paradise, Orr, Antonopoulos, Timos, Nguyen, ThanhVu, Goldwasser, Shafi, Piskac, Ruzica
The correctness of computations remains a significant challenge in computer science, with traditional approaches relying on automated testing or formal verification. Self-testing/correcting programs introduce an alternative paradigm, allowing a progr
Externí odkaz:
http://arxiv.org/abs/2412.18134
Autor:
Perestjuk, Marko, Armand, Rémi, Campos, Miguel Gerardo Sandoval, Ferhat, Lamine, Reboud, Vincent, Bresson, Nicolas, Hartmann, Jean-Michel, Mathieu, Vincent, Ren, Guanghui, Boes, Andreas, Mitchell, Arnan, Monat, Christelle, Grillet, Christian
We report ring resonators on a silicon germanium on silicon platform operating in the mid-infrared wavelength range around 3.5 - 4.6 {\mu}m with quality factors reaching up to one million. Advances in fabrication technology enable us to demonstrate s
Externí odkaz:
http://arxiv.org/abs/2412.10269
Publikováno v:
2021 IEEE International Conference on Image Processing (ICIP), pages 1779-1783, Publication date: 2021/9/19
The aim of multispectral image fusion is to combine object or scene features of images with different spectral characteristics to increase the perceptual quality. In this paper, we present a novel learning-based solution to image fusion problem focus
Externí odkaz:
http://arxiv.org/abs/2412.08073
In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertainty, partic
Externí odkaz:
http://arxiv.org/abs/2412.00056
Autor:
Bertalis, Nerijus, Granse, Paul, Gül, Ferhat, Hauss, Florian, Menkel, Leon, Schüler, David, Speier, Tom, Galke, Lukas, Scherp, Ansgar
Assigning a subset of labels from a fixed pool of labels to a given input text is a text classification problem with many real-world applications, such as in recommender systems. Two separate research streams address this issue. Hierarchical Text Cla
Externí odkaz:
http://arxiv.org/abs/2411.13687
Autor:
Zeiltinger, Julia, Roy, Sushmita, Ay, Ferhat, Mathelier, Anthony, Medina-Rivera, Alejandra, Mahony, Shaun, Sinha, Saurabh, Ernst, Jason
Predicting how genetic variation affects phenotypic outcomes at the organismal, cellular, and molecular levels requires deciphering the cis-regulatory code, the sequence rules by which non-coding regions regulate genes. In this perspective, we discus
Externí odkaz:
http://arxiv.org/abs/2411.04363
Autor:
Miner, Stephen, Takashima, Yoshiki, Han, Simeng, Erata, Ferhat, Antonopoulos, Timos, Piskac, Ruzica, Shapiro, Scott J
Benchmarks are critical for measuring progress of math reasoning abilities of Large Language Models (LLMs). However, existing widely-used benchmarks such as GSM8K have been rendered less useful as multiple cutting-edge LLMs achieve over 94% accuracy.
Externí odkaz:
http://arxiv.org/abs/2410.00151
Autor:
Zoellin, Jay, Merk, Colin, Buob, Mischa, Saad, Amr, Giesser, Samuel, Spitznagel, Tahm, Turgut, Ferhat, Santos, Rui, Zhou, Yukun, Wagner, Sigfried, Keane, Pearse A., Tham, Yih Chung, DeBuc, Delia Cabrera, Becker, Matthias D., Somfai, Gabor M.
Integrating deep learning into medical imaging is poised to greatly advance diagnostic methods but it faces challenges with generalizability. Foundation models, based on self-supervised learning, address these issues and improve data efficiency. Natu
Externí odkaz:
http://arxiv.org/abs/2409.17332
In recent years, neural networks have been used to implement symmetric cryptographic functions for secure communications. Extending this domain, the proposed approach explores the application of asymmetric cryptography within a neural network framewo
Externí odkaz:
http://arxiv.org/abs/2407.08831