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164 results on '"Nandal, Amita"'

6. Brain Tumor Classification via UNET Architecture of CNN Technique

Author

Sharma, Arpit Kumar, Nandal, Amita, Dhaka, Arvind, Bogatinoska, Dijana Capeska, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Joshi, Sandeep, editor, Bairwa, Amit Kumar, editor, Nandal, Amita, editor, Radenkovic, Milena, editor, and Avsar, Cem, editor

Published
2022
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13. Guided Analytics Software for Smart Aggregation, Cognition, and Interactive Visualisation

Author

Karadimce, Aleksandar, Paunkoska (Dimoska), Natasa, Capeska Bogatinoska, Dijana, Marina, Ninoslav, Nandal, Amita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sharma, Manoj Kumar, editor, Dhaka, Vijaypal Singh, editor, Perumal, Thinagaran, editor, Dey, Nilanjan, editor, and Tavares, João Manuel R. S., editor

Published
2021
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14. Classification and Measuring Accuracy of Lenses Using Inception Model V3

Author

Jakhar, Shyo Prakash, Nandal, Amita, Dixit, Rahul, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sharma, Manoj Kumar, editor, Dhaka, Vijaypal Singh, editor, Perumal, Thinagaran, editor, Dey, Nilanjan, editor, and Tavares, João Manuel R. S., editor

Published
2021
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16. Design of Low Power Operational Amplifier for ECG Recording

Author

Dhaka, Arvind, Nandal, Amita, Gangwar, Ajay, Bogatinoska, Dijana Capeska, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Snasel, Vaclav, editor, Platos, Jan, editor, and Hassanien, Aboul Ella, editor

Published
2020
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17. Design of Low-Power and High-Frequency Operational Transconductance Amplifier for Filter Applications

Author

Nandal, Amita, Dhaka, Arvind, Kumar, Nayan, Hadzieva, Elena, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Gupta, Deepak, editor, Bhattacharyya, Siddhartha, editor, Snasel, Vaclav, editor, Platos, Jan, editor, and Hassanien, Aboul Ella, editor

Published
2020
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22. Breast tumor detection using multi‐feature block based neural network by fusion of CT and MRI images.

Author

Kumari, Bersha, Nandal, Amita, and Dhaka, Arvind

Subjects
*BREAST, *IMAGE fusion, *MAGNETIC resonance imaging, *BREAST tumors, *COMPUTED tomography, *IMAGE segmentation
Abstract

Radiologists and clinicians must automatically examine breast and tumor locations and sizes accurately. In recent years, several neural network‐based feature fusion versions have been created to improve medical image segmentation. Multi‐modal image fusion photos may efficiently identify tumors. This work uses image fusion to identify computed tomography and magnetic resonance imaging alterations. A Gauss‐log ratio operator is recommended for difference image production. The Gauss‐log ratio and log ratio difference image complement the objective of improving the difference map through image fusion. The feature change matrix extracts edge, texture, and intensity from each picture pixel. The final change detection map classifies feature vectors as "changed" or "unchanged" which has been mapped for high‐resolution or low‐resolution pixels. This paper proposes a multi‐feature blocks (MFB) based neural network for multi‐feature fusion. This neural network modeling approach globalizes pixel spatial relationships. MFB‐based feature fusion also aims to capture channel interactions between feature maps. The proposed technique outperforms state‐of‐the‐art approaches which have been discussed in detail in experimental results section. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Big Data Analysis

Author

Sharma, Arpit Kumar, primary, Dhaka, Arvind, additional, Nandal, Amita, additional, Swastik, Kumar, additional, and Kumari, Sunita, additional

Published
2021
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29. Contralateral asymmetry for breast cancer detection: A CADx approach

Author

Celaya-Padilla, Jose M., Guzmán-Valdivia, Cesar H., Galván-Tejada, Carlos E., Galván-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Garza-Veloz, Idalia, Martinez-Fierro, Margarita L., Cid-Báez, Miguel A., Martinez-Torteya, Antonio, Martinez-Ruiz, Francisco J., Luna-García, Huizilopoztli, Moreno-Baez, Arturo, and Nandal, Amita

Published
2018
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43. LWT-DCT based Image Watermarking Scheme using Normalized SVD

Author

Dhaka Arvind, Nandal Amita, Dixit Rahul, Varghese Kuriakose Yohan, and Agarwal Vardan

Subjects
Scheme (programming language), General Computer Science, Computer science, business.industry, Singular value decomposition, Discrete cosine transform, Pattern recognition, Artificial intelligence, business, computer, Digital watermarking, Image (mathematics), computer.programming_language
Abstract

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

Published
2021
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