In this study, we propose a new method, named GL-ViT, to integrate both global and local features to fully exploit the few-shot samples for image classification ...
In this study, we propose a new method, named. GL-ViT, to integrate both global and local features to fully exploit the few-shot samples for image ...
In this study, we propose a new method, named GL-ViT, to integrate both global and local features to fully exploit the few-shot samples for image classification ...
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5 days ago · We present a novel method that extends the self-attention mechanism of a vision transformer (ViT) for more accurate object detection across ...
Feb 28, 2024 · We propose in this work a novel model Semantic Filtering Global and Local embeddings for fusion (SFGL) for few-shot image classification.
Few-Shot Image Classification is a computer vision task that involves training machine learning models to classify images into predefined categories.
May 6, 2024 · Approaches based on ViT facilitates the acquisition of both global feature (class token) and local feature (patch token) of an image by ...
Our strategy effectively harnesses the potential of global and local features in few-shot image classification, circumventing the need for complex feature ...
In this paper, we propose SumFS to find global top-ranked sentences by extractive summary and improve the local vocabulary category features.
Oct 30, 2023 · In this notebook, we will utilize multi-backend Keras 3.0 to implement the GCViT: Global Context Vision Transformer paper, presented at ICML 2023.