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 …

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 …

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 …

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 …

Bag-of-words model (BoW), inspired by the problem of text representation and classification,
has attracted intensive attention in object and scene categorization for its flexibility and good …

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 …

Abstract The Bag-of-Visual-Words (BoVW) model is a popular approach for visual
recognition. Used successfully in many different tasks, simplicity and good performance are …

The bag-of-words model has been widely employed in image classification and object
detection tasks. The performance of bag-of-words methods depends fundamentally on the …

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 …

Bag of Visual Words is one of the most effective image representations. One of the
optimization methods for BoVW is the selection of the most informative visual words, which …