Results 191 to 200 of about 15,707 (245)

An object detection and classification method for underwater visual images based on the bag-of-words model

Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 2022
In this study, an autonomous underwater vehicle (AUV) detection technique was used as the background to investigate the target classification method for underwater visual images.
Tianchi Zhang, Qian Li, Xingyu Liu
semanticscholar   +1 more source

Photo Context as a Bag of Words

2008 Tenth IEEE International Symposium on Multimedia, 2008
In the recent years, photo context metadata (e.g.,date, GPS coordinates) have been proved to be useful in the management of personal photos. However, these metadata are still poorly considered in photo retrieving systems. In order to overcome this limitation, we propose an approach to incorporate contextual metadata in a keyword-based photo retrieval ...
Windson Viana, Samira Hammiche, Marlène Villanova-Oliver, Jérôme Gensel, Hervé Martin   +4 more
openaire   +1 more source

Motor Fault Diagnosis Using Image Visual Information and Bag of Words Model

IEEE Sensors Journal, 2021
In order to solve the tough issue that is difficult to extract the representative fault features of the hybrid vibration signals from the various industrial applications, a motor fault diagnosis method based on image visual information and bag of words ...
Zhuo Long, Xiaofei Zhang, Dianyi Song, Yao Tang, Shoudao Huang, Weizhi Liang   +5 more
semanticscholar   +1 more source

BRINGING ORDER IN THE BAG OF WORDS

Proceedings of the International Conference on Computer Vision Theory and Applications, 2012
International audience ; This paper presents a method to infuse spatial information in the bag of words (BOW) framework for object categorization. The main idea is to account the local spatial distribution of the visual words. Rather than finding rigid local patterns, we consider the visual words in close spatial proximity as a pouch of words and we ...
Zhang, Shihong, Khan, Rahat, Muselet, Damien, Trémeau, A.   +3 more
openaire   +2 more sources

Distinguish Polarity in Bag-of-Words Visualization

Proceedings of the AAAI Conference on Artificial Intelligence, 2017
Neural network-based BOW models reveal that word-embedding vectors encode strong semantic regularities. However, such models are insensitive to word polarity. We show that, coupled with simple information such as word spellings, word-embedding vectors can preserve both semantic regularity and conceptual polarity without supervision. We
Yusheng Xie, Zhengzhang Chen, Ankit Agrawal 0001, Alok N. Choudhary   +3 more
openaire   +1 more source

CLIP Behaves like a Bag-of-Words Model Cross-modally but not Uni-modally

arXiv.org
CLIP (Contrastive Language-Image Pretraining) has become a popular choice for various downstream tasks. However, recent studies have questioned its ability to represent compositional concepts effectively.
Darina Koishigarina, Arnas Uselis, S. Oh
semanticscholar   +1 more source

Contextual Bag-of-Words for Visual Categorization

IEEE Transactions on Circuits and Systems for Video Technology, 2011
Bag-of-words (BOW), which represents an image by the histogram of local patches on the basis of a visual vocabulary, has attracted intensive attention in visual categorization due to its good performance and flexibility. Conventional BOW neglects the contextual relations between local patches due to its Naive Bayesian assumption.
Li, T Li, Teng, Mei, T Mei, Tao, Kweon, IS Kweon, In-So, Hua, XS Hua, Xian-Sheng   +3 more
openaire   +1 more source

Comparing Bag-of-Words, SBERT, and GPT-3 for Bias Detection

Journal of student-scientists' research
This project aims to detect bias in media by training a machine learning model to recognize biased sentences. We did this by using a dataset containing 3700 sentences each annotated by multiple experts.
Max Luo, Clayton Greenberg
semanticscholar   +1 more source

Context Dependent Bag of words generation

2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013
Query spelling correction is a crucial component in modern text mining systems such as Question-answering systems and Sentiment Analysis systems where noise can affect the query matching score. In many existing query matching systems Bag of Words (BoW) generation method is used to generate candidates for noisy words.
Swapnil Ashok Jadhav, Durvasula V. L. N. Somayajulu, S. Nagesh Bhattu, R. B. V. Subramanyam, P. Suresh   +4 more
openaire   +1 more source

Bag-of-words representations for computer audition.

2022
Maschinelles Hören ist im täglichen Leben allgegenwärtig, mit Anwendungen, die von personalisierten virtuellen Agenten bis hin zum Gesundheitswesen reichen. Aus technischer Sicht besteht das Ziel darin, den Inhalt eines Audiosignals hinsichtlich einer Auswahl definierter Labels robust zu klassifizieren. Die Labels beschreiben bspw.
openaire   +3 more sources