Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Aneja, Sandhya"'
Autor:
Jatana, Nishtha, Singh, Mansehej, Gupta, Charu, Dhand, Geetika, Malik, Shaily, Dadheech, Pankaj, Aneja, Nagender, Aneja, Sandhya
Publikováno v:
Multimedia Tools and Applications (2024)
A collaborative real-time text editor is an application that allows multiple users to edit a document simultaneously and merge their contributions automatically. It can be made collaborative by implementing a conflict resolution algorithm either on t
Externí odkaz:
http://arxiv.org/abs/2407.03027
Publikováno v:
IAES International Journal of Artificial Intelligence (IJ-AI), Vol. 11, No. 4, December 2022, pp. 1252~1260
Media news are making a large part of public opinion and, therefore, must not be fake. News on web sites, blogs, and social media must be analyzed before being published. In this paper, we present linguistic characteristics of media news items to dif
Externí odkaz:
http://arxiv.org/abs/2211.14505
Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising
Publikováno v:
IAES International Journal of Artificial Intelligence, Vol. 11, No. 3, September 2022, pp. 961~968, ISSN: 2252-8938
Despite substantial advances in network architecture performance, the susceptibility of adversarial attacks makes deep learning challenging to implement in safety-critical applications. This paper proposes a data-centric approach to addressing this p
Externí odkaz:
http://arxiv.org/abs/2206.12685
Publikováno v:
IAES International Journal of Artificial Intelligence (IJ-AI), Vol. 11, No. 1, March 2022, pp. 129~136
Transfer learning allows us to exploit knowledge gained from one task to assist in solving another but relevant task. In modern computer vision research, the question is which architecture performs better for a given dataset. In this paper, we compar
Externí odkaz:
http://arxiv.org/abs/2112.15523
Artificial Intelligence (AI) development has encouraged many new research areas, including AI-enabled Internet of Things (IoT) network. AI analytics and intelligent paradigms greatly improve learning efficiency and accuracy. Applying these learning p
Externí odkaz:
http://arxiv.org/abs/2112.12546
Publikováno v:
International Conference on Big Data and Internet of Things (BDIOT2020), August 22-24, 2020
Device identification is the process of identifying a device on Internet without using its assigned network or other credentials. The sharp rise of usage in Internet of Things (IoT) devices has imposed new challenges in device identification due to a
Externí odkaz:
http://arxiv.org/abs/2009.04682
Publikováno v:
International Conference on Natural Language Processing (ICNLP 2020), July 11-13, 2020
Machine translation has many applications such as news translation, email translation, official letter translation etc. Commercial translators, e.g. Google Translation lags in regional vocabulary and are unable to learn the bilingual text in the sour
Externí odkaz:
http://arxiv.org/abs/2007.16011
Autor:
Aneja, Nagender, Aneja, Sandhya
Publikováno v:
IEEE International Conference on Advances in Information Technology (ICAIT), ICAIT - 2019
This paper presents an analysis of pre-trained models to recognize handwritten Devanagari alphabets using transfer learning for Deep Convolution Neural Network (DCNN). This research implements AlexNet, DenseNet, Vgg, and Inception ConvNet as a fixed
Externí odkaz:
http://arxiv.org/abs/1909.08774
Device Fingerprinting (DFP) is the identification of a device without using its network or other assigned identities including IP address, Medium Access Control (MAC) address, or International Mobile Equipment Identity (IMEI) number. DFP identifies a
Externí odkaz:
http://arxiv.org/abs/1902.01926
Autor:
Semalti, Kapil, Sharma, Vivek, Kumar, Vivek, Aneja, Sandhya, Simalti, Ashish K., Malik, Akash
Publikováno v:
In Medical Journal Armed Forces India October 2022