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 …

Although traditional image classification techniques are often used in authentic ways, they
have several drawbacks, such as unsatisfactory results, poor classification accuracy, and a …

Bag of Visual Words model is widely used for image classification nowadays. When
combined with machine learning approach, it has shown remarkable results for image …

Image classification is one of the most significant and challenging tasks in computer vision.
The goal of this task is to build a system that is capable to reveal an image label within a …

In this paper two main stages for image classification has been presented. Training stage
consists of collecting images of interest, and apply BOVW on these images (features …

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 …

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 feature representation by bag-of-visual words (BOVW) has been widely considered in
the image classification related problems. The feature extraction step is usually based on …

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