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Found 11 papers, 2 papers with code
Inherent limitations of LLMs regarding spatial information
Despite the significant advancements in natural language processing capabilities demonstrated by large language models such as ChatGPT, their proficiency in comprehending and processing spatial information, especially within the domains of 2D and 3D route planning, remains notably underdeveloped.
Nonlinear Multi-Carrier System with Signal Clipping: Measurement, Analysis, and Optimization
With the derivations, we investigate the optimal system setting to achieve the SER lower bound in a practical OFDM system that considers both PA nonlinearity and clipping distortion.
Digital staining in optical microscopy using deep learning -- a review
Until recently, conventional biochemical staining had the undisputed status as well-established benchmark for most biomedical problems related to clinical diagnostics, fundamental research and biotechnology.
Imaging across multiple spatial scales with the multi-camera array microscope
This article experimentally examines different configurations of a novel multi-camera array microscope (MCAM) imaging technology.
Tensorial tomographic differential phase-contrast microscopy
We report Tensorial Tomographic Differential Phase-Contrast microscopy (T2DPC), a quantitative label-free tomographic imaging method for simultaneous measurement of phase and anisotropy.
Transient motion classification through turbid volumes via parallelized single-photon detection and deep contrastive embedding
We evaluate our setup by classifying different spatiotemporal-decorrelating patterns hidden beneath a 5mm tissue-like phantom made with rapidly decorrelating dynamic scattering media.
Increasing a microscope's effective field of view via overlapped imaging and machine learning
This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis.
Imaging dynamics beneath turbid media via parallelized single-photon detection
Noninvasive optical imaging through dynamic scattering media has numerous important biomedical applications but still remains a challenging task.
Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning
Few-shot text classification is a fundamental NLP task in which a model aims to classify text into a large number of categories, given only a few training examples per category.
Text Augmentation in a Multi-Task View
Traditional data augmentation aims to increase the coverage of the input distribution by generating augmented examples that strongly resemble original samples in an online fashion where augmented examples dominate training.
Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm
The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm.
