Risultati della ricerca - coding (algorithm OR algorithmssics)

X-Shooting ULLYSES: Massive stars at low metallicity. IV. Spectral analysis methods and exemplary results for O stars di Sander, A. A. C., Bouret, J. -C., Bernini-Peron, M., Puls, J., Backs, F., Berlanas, S. R., Bestenlehner, J. M., Brands, S. A., Herrero, A., Martins, F., Maryeva, O., Pauli, D., Ramachandran, V., Crowther, P. A., Gómez-González, V. M. A., Gormaz-Matamala, A. C., Hamann, W. -R., Hillier, D. J., Kuiper, R., Larkin, C. J. K., Lefever, R. R., Mehner, A., Najarro, F., Oskinova, L. M., Schösser, E. C., Shenar, T., Todt, H., ud-Doula, A., Vink, J. S.

Sommario: “... Sk -69 50, and LMC O9 star Sk -66 171), we employ different atmosphere codes (CMFGEN, Fastwind, PoWR...”
Testo

reBEN: Refined BigEarthNet Dataset for Remote Sensing Image Analysis di Clasen, Kai Norman, Hackel, Leonard, Burgert, Tom, Sumbul, Gencer, Demir, Begüm, Markl, Volker

Sommario: “.... Furthermore, we introduce a new geographical-based split assignment algorithm that significantly reduces...”
Testo

An activity transition in FRB 20201124A: methodological rigor, detection of frequency-dependent cessation, and a geometric magnetar model di Bilous, A. V., van Leeuwen, J., Maan, Y., Pastor-Marazuela, I., Oostrum, L. C., Rajwade, K. M., Wang, Y. Y.

Sommario: “... algorithms. Our investigations of fluence distributions next lead us to advise against formal power-law...”
Testo

Nonrigid Reconstruction of Freehand Ultrasound without a Tracker di Li, Qi, Shen, Ziyi, Yang, Qianye, Barratt, Dean C., Clarkson, Matthew J., Vercauteren, Tom, Hu, Yipeng

Sommario: “... novel co-optimisation algorithm for simultaneously estimating rigid transformations among US frames...”
Testo

Empirical mass-loss rates and clumping properties of O-type stars in the LMC di Hawcroft, C., Mahy, L., Sana, H., Sundqvist, J. O., Abdul-Masih, M., Brands, S. A., Decin, L., deKoter, A., Puls, J.

Sommario: “... atmosphere modelling code FASTWIND, and reproduce the observed spectra using a genetic algorithm based...”
Testo

Safe-SD: Safe and Traceable Stable Diffusion with Text Prompt Trigger for Invisible Generative Watermarking di Ma, Zhiyuan, Jia, Guoli, Qi, Biqing, Zhou, Bowen

Sommario: “... Stable Diffusion framework (namely Safe-SD) to adaptively implant the graphical watermarks (e.g., QR code...”
Testo

Image-text matching for large-scale book collections di Llabrés, Artemis, Dey, Arka Ujjal, Karatzas, Dimosthenis, Valveny, Ernest

Sommario: “... outperform a fuzzy string matching baseline, and we highlight inherent limitations of the matching algorithms...”
Testo

Towards pedestrian head tracking: A benchmark dataset and a multi-source data fusion network di Sun, Kailai, Wang, Xinwei, Liu, Shaobo, Zhao, Qianchuan, Huang, Gao, Liu, Chang

Sommario: “.... Existing state-of-the-art (SOTA) algorithms are tested and compared on the Cchead dataset. MDFN...”
Testo

One Homography is All You Need: IMM-based Joint Homography and Multiple Object State Estimation di Claasen, Paul Johannes, de Villiers, Johan Pieter

Sommario: “...A novel online MOT algorithm, IMM Joint Homography State Estimation (IMM-JHSE), is proposed. IMM...”
Testo

Robot Utility Models: General Policies for Zero-Shot Deployment in New Environments di Etukuru, Haritheja, Naka, Norihito, Hu, Zijin, Lee, Seungjae, Mehu, Julian, Edsinger, Aaron, Paxton, Chris, Chintala, Soumith, Pinto, Lerrel, Shafiullah, Nur Muhammad Mahi

Sommario: “... training algorithm and policy class, guidance about data scaling, necessity for diverse yet high-quality...”
Testo

PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images di Liu, Nanqing, Xu, Xun, Su, Yongyi, Zhang, Haojie, Li, Heng-Chao

Sommario: “... dataset and use the Hungarian algorithm to match them with prediction prototypes, preventing the model...”
Testo

HazeSpace2M: A Dataset for Haze Aware Single Image Dehazing di Islam, Md Tanvir, Rahim, Nasir, Anwar, Saeed, Saqib, Muhammad, Bakshi, Sambit, Muhammad, Khan

Sommario: “... diverse haze types, impeding effective haze type classification and dehazing algorithm selection...”
Testo

TestBench: Evaluating Class-Level Test Case Generation Capability of Large Language Models di Zhang, Quanjun, Shang, Ye, Fang, Chunrong, Gu, Siqi, Zhou, Jianyi, Chen, Zhenyu

Sommario: “...: syntactic correctness, compilation correctness, test correctness, code coverage rate, and defect detection...”
Testo

FAST: A Dual-tier Few-Shot Learning Paradigm for Whole Slide Image Classification di Fu, Kexue, Luo, Xiaoyuan, Qu, Linhao, Wang, Shuo, Xiong, Ying, Maglogiannis, Ilias, Gao, Longxiang, Wang, Manning

Sommario: “... for the widespread adoption of deep learning-based Whole Slide Images (WSI) classification algorithms in clinical...”
Testo

V2I-Calib++: A Multi-terminal Spatial Calibration Approach in Urban Intersections for Collaborative Perception di Qu, Qianxin, Zhang, Xinyu, Cheng, Yifan, Xiong, Yijin, Xia, Chen, Peng, Qian, Song, Ziqiang, Liu, Kang, Wu, Xin, Li, Jun

Sommario: “... global consistency search algorithms with optimal transport theory. By this means, we can extract co...”
Testo

Identifying General Mechanism Shifts in Linear Causal Representations di Chen, Tianyu, Bello, Kevin, Locatello, Francesco, Aragam, Bryon, Ravikumar, Pradeep

Sommario: “... observed data. Our algorithm lends itself very naturally to the sample setting where instead of just...”
Testo

You are out of context! di Cobino, Giancarlo, Farci, Simone

Sommario: “... algorithms, and parallelization for real-time and large-scale applications. The method's effectiveness...”
Testo

SA3DIP: Segment Any 3D Instance with Potential 3D Priors di Yang, Xi, Gu, Xu, Yin, Xingyilang, Gao, Xinbo

Sommario: “... geometry. Besides, the heavy reliance on SAM and hand-crafted algorithms in 2D space suffers from over...”
Testo

HOPE: An Automatically Differentiable High-Order Non-Oscillatory Finite-Volume Shallow-Water Dynamic Core di Zhou, Lilong

Sommario: “...: high order accuracy, essential non-oscillation, mass conservation, and scalability. Besides, the code...”
Testo

YOLO-CCA: A Context-Based Approach for Traffic Sign Detection di Jiang, Linfeng, Zhan, Peidong, Bai, Ting, Yu, Haoyong

Sommario: “... algorithm for traffic sign detection, which utilizes YOLOv7 as the baseline model. Firstly, we propose...”
Testo