output
20062026
most citedEnsemble deep learning: A review

2.2k citations

1,105 papers

cs.CV2026

Uncertainty-Aware Semi-Supervised Framework with Supervised Contrastive Learning for Sugarcane Leaf Disease Detection

Shalini Dangi, Divya Teja, Omkar Kabde +2

Sugarcane leaf diseases severely impact crop yield and quality, making accurate and timely detection critical for sustainable agriculture. Conventional deep learning models for pla…

astro-ph.GA2026

Finding the evolutionary link between ULIRGs and radio galaxies

Ayisha Fida, Sumana Nandi, Mousumi Das +4

Ultraluminous infrared galaxies (ULIRGs) are the remnants of the major mergers of gas-rich galaxies. They are dusty systems and are extremely luminous in the infrared. Both starbur…

astro-ph.HE2026

The Impact of a Clumpy Ambient Medium on the Dynamics and Synchrotron Emission of AGN Jets

Ivan Almeida, Christian Fendt, Bhargav Vaidya

Relativistic jets from AGN are expected to propagate through an inhomogeneous ISM, but the role of small-scale gas inhomogeneities in shaping their early evolution remains uncertai…

cond-mat.str-el2026

Asymmetric magnetoresistance in 3-5 based LaCaMnO/SrIrO bilayer: The role of unidirectional anisotropy

A. G. A. Rahman, Subham Naskar, R. K. Patel +4

The complex interplay between spin-orbit coupling, magnetism, and magnetic field at the interface of a heterostructure consisting of ferromagnet (FM) and heavy metal (HM), often ex…

cs.NI2026

Key Reconciliation with RC-LDPC/Error Estimation for Satellite-based FSO/QKD Systems

Cuong T. Nguyen, Hoang D. Le, Anshul Jaiswal +2

Satellite-based free-space optics (FSO) quantum key distribution (QKD) systems have recently attracted significant research interest due to their potential to enable globally secur…

cs.LG2026★ 2 cited

LLMs as Master Forgers: Generating Synthetic Time Series Data for Manufacturing

Mantek Singh, Jeshwanth Challagundla, Prateek Karnal +3

This paper presents a novel framework leveraging Large Language Models (LLMs) to generate synthetic time series data for manufacturing processes. Motivated by the scarcity of label…