Bag of words (BOW) model is widely applied in image classification. The traditional BOW
neglects the spatial information and object shape information, which fails to distinguish …

Today, image classification is considered as one of the most important and challenging
tasks in computer vision. This paper presents a new method for image classification using …

Abstract The Bag of Words (BoW) model is applied to object classification in this paper. An
optimized method based on the combination of Region Of Interest (ROI) extraction and …

Bag of visual words model has recently attracted much attention from computer vision
society because of its notable success in analysing images and exploring their content. This …

Image classification is a method that distinguishes the different categories of targets based
on the different features of image. The current problem usually is that the feature modeling of …

Bag-of-words is a classical method for image classification. The core problem is how to
count the frequency of the visual words and what visual words to select. In this paper, we …

In the image classification field, the visual bag of words (BoW) has two drawbacks. One is
low classification accuracy because a visual BoW is typically extracted from local low-level …

Based on traditional bag of words model and combined with the features of human visual,
an improved image classification method is proposed in this paper. Firstly, compute the …

The bag of visual words (BOW) model has been widely applied in the field of image
recognition and image classification. However, all scale‐invariant feature transform (SIFT) …

Image classification is acknowledged as one of the most critical and challenging tasks in
computer vision. The bag of visual words (BoVW) model has proven to be very efficient for …