| |
|
|
| |
| |
|
Date Reviewed |
|
| |
1 - 5 of 5
reviews
|
|
|
 |
|
|
|
|
 A survey on deep neural network-based image captioning
Liu X., Xu Q., Wang N. The Visual Computer 35(3): 445-470, 2019. Type: Article, Reviews: (2 of 2)
Image captioning is an intriguing problem in the field of computer vision: given an input image, come up with suitable concise text that verbalizes that image well. This is currently a hot topic in the context of image understanding, a...
|
Jun 29 2020 |
|
|
|
|
|
|
ELSA: a multilingual document summarization algorithm based on frequent itemsets and latent semantic analysis
Cagliero L., Garza P., Baralis E. ACM Transactions on Information Systems 37(2): 1-33, 2019. Type: Article, Reviews: (1 of 2)
Multi-document summarization involves the automatic generation of concise summaries of a number of textual documents, with the goal of succinctly presenting the most salient information. This allows readers to get the main idea without...
|
Jan 16 2020 |
|
|
|
|
|
|
Characterizing and predicting individual traffic usage of mobile application in cellular network
Wu J., Zeng M., Chen X., Li Y., Jin D. UbiComp 2018 (Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, Singapore, Oct 8-12, 2018) 852-861, 2018. Type: Proceedings
The ubiquitous use of smart devices all over the world has contributed to an explosive increase in network traffic. Thus, methods for characterizing and predicting application-level traffic patterns from both individual and operator pe...
|
Jan 25 2019 |
|
|
|
|
|
|
Making machine learning robust against adversarial inputs
Goodfellow I., McDaniel P., Papernot N. Communications of the ACM 61(7): 56-66, 2018. Type: Article
Machine learning (ML) has become ubiquitous in recent times. It is used in numerous (important) applications and its use will seemingly only increase. The current ML state of the art can be attributed to “nearly 50 years of r...
|
Oct 15 2018 |
|
|
|
|
|
|
Support vector machines and perceptrons: learning, optimization, classification, and application to social networks
Murty M., Raghava R., Springer International Publishing, New York, NY, 2016. 95 pp. Type: Book (978-3-319410-62-3)
In the preface of the book, the authors boldly state: “SVMs [support vector machines] have revolutionized the research in the areas of machine learning and pattern recognition, specifically classification, so much that for a ...
|
Apr 11 2017 |
|
|
|
|
|
| |
|
|
| |
|
|
