Search Results for author:
Found 7 papers, 4 papers with code
Hyperbolic Learning with Synthetic Captions for Open-World Detection
Specifically, we bootstrap dense synthetic captions using pre-trained VLMs to provide rich descriptions on different regions in images, and incorporate these captions to train a novel detector that generalizes to novel concepts.
Neural Insights for Digital Marketing Content Design
In digital marketing, experimenting with new website content is one of the key levers to improve customer engagement.
Efficient Classification of Very Large Images with Tiny Objects
Specifically, these classification tasks face two key challenges: $i$) the size of the input image is usually in the order of mega- or giga-pixels, however, existing deep architectures do not easily operate on such big images due to memory constraints, consequently, we seek a memory-efficient method to process these images; and $ii$) only a very small fraction of the input images are informative of the label of interest, resulting in low region of interest (ROI) to image ratio.
Quantum Tensor Network in Machine Learning: An Application to Tiny Object Classification
In the end, our experimental results indicate that tensor network models are effective for tiny object classification problem and potentially will beat state-of-the-art.
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models
Deep neural networks excel at comprehending complex visual signals, delivering on par or even superior performance to that of human experts.
Physics-enhanced machine learning for virtual fluorescence microscopy
This paper introduces a new method of data-driven microscope design for virtual fluorescence microscopy.
The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation
Recently deep learning - namely convolutional neural networks (CNNs) - have yielded impressive performance for the task of building segmentation on large overhead (e. g., satellite) imagery benchmarks.
