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 …

Methods based on the Bag-Of-Words (BoW) model have made a remarkable success in
image classification, but many of which do not consider the structure underlying in the …

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 …

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

This paper presents a new framework for visual bag-of-words (BOW) refinement and
reduction to overcome the drawbacks associated with the visual BOW model which has …

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 …

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 …

In the problem where there is not enough data to use Deep Learning, Bag-of-Visual-Words
(BoVW) is still a good alternative for image classification. In BoVW model, many pooling …

Image Classification based on BOW (Bag-of-words) has broad application prospect in
pattern recognition field but the shortcomings are existed because of single feature and low …