Author details

< Back

Nagamma Patil

Publications

Citations

219

Publications by Year

20142024

Co-Authors:

Shubham AgrawalR. C. AnirudhaSanjay BankapurChirag BavishiJaidhar C. D.

Show All Co-Authors (46)

Nagamma Patil

Affiliation

Information Technology

NITK

Surathkal, Karnataka

Publication Topics

Convolutional Neural Network,
Deep Learning,
Machine Learning,
Deep Learning Models,
Neural Network,
Learning Algorithms,
Machine Learning Models,
Convolutional Neural Network Model,
Deep Neural Network,
Disease Detection,
Leaf Images,
Long Short-term Memory

Biography

Nagamma Patil received the Ph.D. degree in computer science and engineering from the Indian Institute of Technology Roorkee, India. She is with the Department of Information Technology, National Institute of Technology Karnataka, Surathkal, India. Her research interests include data mining, soft computing, big data analytics, machine learning, and bioinformatics.(Based on document published on 27 December 2021).

Publications

Citations

219

Publications by Year

20142024

Co-Authors:

Shubham Agrawal
R. C. Anirudha
Sanjay Bankapur
Chirag Bavishi
Jaidhar C. D.

Show All Co-Authors (46)

Author's Published Works

Search History

Showing 1-9 of 9 results

Conferences (9)

Sort

Filter Results

Show

All Results

Subscribed Content

Open Access Only

Range
Single Year
Mohamed Atri(8)
Wajdi Elhamzi(8)
Wadhah Ayadi(5)
Ayoub Mhaouch(2)
R. Tourki(1)
College of Computer Science, King Khalid University, Abha, Saudi Arabia(5)
College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-kharj, Saudi Arabia(3)
Higher School of Sciences and Technology of Hammam Sousse, University of Sousse, Tunisia(2)
Laboratory of Electronics and Microelectronics, Faculty of Sciences of Monastir, University of Monastir, Tunisia(2)
College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia(2)
2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)(2)
2008 2nd International Conference on Signals, Circuits and Systems(1)
2016 International Image Processing, Applications and Systems (IPAS)(1)
2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET)(1)
2020 20th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)(1)
IEEE(9)
Hammamet, Tunisia(6)
Monastir, Tunisia(1)
Nabeul, Tunisia(1)
Sousse, Tunisia(1)
Magnetic Resonance Imaging(4)
Clock Cycles(3)
Convolutional Layers(3)
Acceptable Results(2)
Block Cipher(2)

Select All on Page

Sort By

Results

Efficient Serial Architecture for PRESENT Block Cipher

Ayoub Mhaouch;Wajdi Elhamzi;Abdessalem Ben Abdelali;Mohamed Atri

2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

Year: 2022 | Conference Paper |

Cited by: Papers (5)

HTML

In recent years, the use of the Internet of Things (IoT) has increased rapidly in different areas. Due to many IoT applications, many limitations have emerged such as power consumption and limited resources. The security of connected devices is becoming more and more a primary need for the reliability of systems. Among other things, power consumption remains an essential constraint with a major im...Show More

Efficient Serial Architecture for PRESENT Block Cipher

Ayoub Mhaouch;Wajdi Elhamzi;Abdessalem Ben Abdelali;Mohamed Atri

2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

Year: 2022 | Conference Paper |

Multi-Classification of brain tumor based on deep CNN

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

Year: 2022 | Conference Paper |

HTML

In the last decades, brain tumors are considered one of the mortal cancers in the world. The right tumors detection and identification in the early phases have a significant role to select an accurate treatment. Due to the increasing number of patients and brain tumor types, the manual analyses of Magnetic Resonance Imaging (MRI) images represent a tiring routine and can lead to human errors. In t...Show More

Multi-Classification of brain tumor based on deep CNN

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

Year: 2022 | Conference Paper |

Glioma segmentation based on deep CNN

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)

Year: 2022 | Conference Paper |

HTML

Brain tumor segmentation represents a hard job for radiologists as the brain is the most complicated and complex organ. Among the several brain tumors that existed, gliomas are the most aggressive and common. They lead to a short life in their highest grade especially. It is usually the most found tumors, which have various shapes, sizes, and brightness. It can appear anywhere in the brain. These ...Show More

Glioma segmentation based on deep CNN

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)

Year: 2022 | Conference Paper |

A new deep CNN for brain tumor classification

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2020 20th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

Year: 2020 | Conference Paper |

Cited by: Papers (5)

HTML

In the last years, the brain tumor is considered as one of the most deadly tumors around the world. It can affect adults and children. The wrong classification of the tumor brain will lead to bad consequences. Consequently, the right identification of the type and the grade of tumors in the early stages has a significant role to choose a precise treatment plan. Due to the various brain tumor types...Show More

A new deep CNN for brain tumor classification

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2020 20th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

Year: 2020 | Conference Paper |

Lightweight Hardware Architectures for the Piccolo Block Cipher in FPGA

Ayoub Mhaouch;Wajdi Elhamzi;Mohamed Atri

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

Year: 2020 | Conference Paper |

Cited by: Papers (8)

HTML

The Piccolo block cipher is a lightweight block encryption for hardware use. Hardware devices are equipped with limited computation resources and small memory. In this paper, we propose an implementation to carry out through several trade-offs between area and speed. We implemented the Piccolo block cipher algorithm with 128-bit key in two different architectures on FPGA: the iterative and the 4-b...Show More

Lightweight Hardware Architectures for the Piccolo Block Cipher in FPGA

Ayoub Mhaouch;Wajdi Elhamzi;Mohamed Atri

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

Year: 2020 | Conference Paper |

Brain MRI classification using discrete wavelet transform and bag-of-words

Wadhah Ayadi;Wajdi Elhamzi;Imen Charfi;Bouraoui Ouni;Mohamed Atri

2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET)

Year: 2018 | Conference Paper |

Cited by: Papers (5)

HTML

Automatic CAD system able to detect correctly the unhealthy brain in magnetic resonance imaging (MRI) scanning is represented in this paper. The new system exploited Discrete Wavelet Transform (DWT) and Bag-of-Words (BoW) to extract image features. Support vector machine (SVM) was used in classification step. We employed 256×256 images from three datasets (DS-66, DS-160, DS-255) provided by Harvar...Show More

Brain MRI classification using discrete wavelet transform and bag-of-words

Wadhah Ayadi;Wajdi Elhamzi;Imen Charfi;Bouraoui Ouni;Mohamed Atri

2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET)

Year: 2018 | Conference Paper |

A FPGA-based implementation of JPEG encoder

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2016 International Image Processing, Applications and Systems (IPAS)

Year: 2016 | Conference Paper |

Cited by: Papers (1)

HTML

The research in the domain of image compression increased significantly where the requirements of transmission images have raised enormously. Image compression is very important in digital image processing. It plays a crucial role in efficient transmission and storage of images. The most widely used method of lossy compression is JPEG standard. In this paper, we will discuss the implementation of ...Show More

A FPGA-based implementation of JPEG encoder

Wadhah Ayadi;Wajdi Elhamzi;Mohamed Atri

2016 International Image Processing, Applications and Systems (IPAS)

Year: 2016 | Conference Paper |

An efficient hardware implementation of Diamond Search motion estimation using CAL dataflow language

Wajdi Elhamzi;Richard Thavot;Julien Dubois;Jérôme Gorin;Mohamed Atri;Johel Miteran;Rached Tourki

ICM 2011 Proceeding

Year: 2011 | Conference Paper |

Cited by: Papers (2)

HTML

Motion estimation represents a key module in video compression. The Reconfigurable Video Coding context (RVC) requires proposing a flexible solution for motion estimation. The motion estimation performance should be modified to fit with the user or the environment's constraints. Depending on the required performances fixed by the application, a full search is sometimes not suitable, hence, alterna...Show More

An efficient hardware implementation of Diamond Search motion estimation using CAL dataflow language

Wajdi Elhamzi;Richard Thavot;Julien Dubois;Jérôme Gorin;Mohamed Atri;Johel Miteran;Rached Tourki

ICM 2011 Proceeding

Year: 2011 | Conference Paper |

On Hardware Implementation of DCT/IDCT for Image Processing

W. Elhamzi;T. Saidani;M. Atri;R. Tourki

2008 2nd International Conference on Signals, Circuits and Systems

Year: 2008 | Conference Paper |

HTML

Most studies on standards of image and video compression demonstrated the need to rely on hardware accelerator for the most computationally intensive part of the coding process that is the discrete cosine transform (DCT). In this paper, a material implementation of discrete cosine transform (DCT) and inverse DCT (IDCT) was presented, in the goal to reduce execution time and chip size. Also to achi...Show More

On Hardware Implementation of DCT/IDCT for Image Processing

W. Elhamzi;T. Saidani;M. Atri;R. Tourki

2008 2nd International Conference on Signals, Circuits and Systems

Year: 2008 | Conference Paper |

MIT Libraries

MIT Libraries

Author details

Nagamma Patil

Nagamma Patil

Affiliation

Publication Topics

Biography

Showing 1-9 of 9 results

Show

Efficient Serial Architecture for PRESENT Block Cipher

Efficient Serial Architecture for PRESENT Block Cipher

Multi-Classification of brain tumor based on deep CNN

Multi-Classification of brain tumor based on deep CNN

Glioma segmentation based on deep CNN

Glioma segmentation based on deep CNN

A new deep CNN for brain tumor classification

A new deep CNN for brain tumor classification

Lightweight Hardware Architectures for the Piccolo Block Cipher in FPGA

Lightweight Hardware Architectures for the Piccolo Block Cipher in FPGA

Brain MRI classification using discrete wavelet transform and bag-of-words

Brain MRI classification using discrete wavelet transform and bag-of-words

A FPGA-based implementation of JPEG encoder

A FPGA-based implementation of JPEG encoder

An efficient hardware implementation of Diamond Search motion estimation using CAL dataflow language

An efficient hardware implementation of Diamond Search motion estimation using CAL dataflow language

On Hardware Implementation of DCT/IDCT for Image Processing

On Hardware Implementation of DCT/IDCT for Image Processing

IEEE Account

Purchase Details

Profile Information

Need Help?