Browsing by Author "Joshi, Manjunath V."

Now showing items 1-20 of 50

    • Attack on Network Traffic Classification 

      kumar, Pushpender (Dhirubhai Ambani Institute of Information and Communication Technology, 2022)
      Various network traffic management and intrusion detection solutions use network traffic classification. Machine Learning (ML), while deep learning (DL)-based models, had exhibited excellent performance in Internet traffic ...

    • Automatic image inpainting for the facial images of monuments 

      Parmar, Chintan (Dhirubhai Ambani Institute of Information and Communication Technology, 2011)
      Image inpainting is the process of restoring or modifying the image contents im- perceptibly. In this paper we propose a novel approach for automatic image inpainting of the ruined frontal face images of monuments or ...

    • Automatic target image detection for morphing 

      Vyas, Jaladhi (Dhirubhai Ambani Institute of Information and Communication Technology, 2013)
      In this thesis,we propose a novel approach for automatic target image detection for morphing based on 3D textons and contrast. Given the source image consisting of human frontal face and training images having human and ...

    • Automatic Text Translation of Multilingual Sentences using Transformer 

      Hari Charan, Edara Veera Venkata (Dhirubhai Ambani Institute of Information and Communication Technology, 2022)
      Machine translation from one language to another is a complex problem in machine learning and one in which the machine still cannot achieve satisfactory results. The recent focus for solving this challenge has been on ...

    • Blind inpainting and super-resolution using convolutional neural network 

      Sohoney, Surabhi (Dhirubhai Ambani Institute of Information and Communication Technology, 2016)
      In this work, we propose a combined approach to two image processing problems:Image Inpainting and Image Super-Resolution(SR). A number of efficient techniqueshave been developed for solving these two problems using deep ...

    • Channel estimation in OFDM systems 

      Rathore, Hitesh (Dhirubhai Ambani Institute of Information and Communication Technology, 2010)
      Orthogonal frequency division multiplexing (OFDM) is not a new concept, but its receiver design has constant improvement. OFDM uses available spectrum efficiently and the system provides high data rates. Many standards ...

    • Deep learning based image super-resolution 

      Madhu, Prathmesh Rajesh (Dhirubhai Ambani Institute of Information and Communication Technology, 2016)
      Super-resolution is an algorithmic approach to increase the spatial resolution ofan image. In areas like medical imaging, satellite image processing, biometrics,robotics, text to speech conversion, optical character ...

    • Dense disparity estimation using stereo images 

      Nahar, Sonam (Dhirubhai Ambani Institute of Information and Communication Technology, 2017)
      "“Stereo vision” refers to the ability to infer information on the three-dimensional (3D) structure and distance/depth of a scene using two images captured from different view-points. It imitates one of the tasks performed ...

    • Disparity estimation by stereo using particle swarm optimization and graph cuts 

      Nahar, Sonam (Dhirubhai Ambani Institute of Information and Communication Technology, 2010)
      Stereo vision is based on the process of obtaining the disparity from a left and a right view of a scene. By obtaining the disparity, we find the distance (depth) of each object point from the camera so that we can construct ...

    • Document Language Classification Using Deep Learning Approaches 

      Shah, Sarathi Surendra (2021)
      Optical character recognition (OCR) refers to the task of recognizing the characters or text from digital document images. OCR is a widely researched area for the past many years due to its applications in various fields. ...

    • Human Action Recognition Using Deep Neural Networks 

      Thakkar, Shaival (Dhirubhai Ambani Institute of Information and Communication Technology, 2017)
      "In this thesis, we present a hierarchical approach for human action classification using 3-D Convolutional neural networks (3-D CNN). Human actions refer to positioning and movement of hands and legs and hence can be ...

    • Image compression using DCT and compressive sensing (CS) theory 

      Jain, Archit (Dhirubhai Ambani Institute of Information and Communication Technology, 2014)
      Data compression is a method of storing the same information with less data or space. There are many techniques available for compressing the image data resulting in reduced storage space. Minimizing storage space minimizes ...

    • Imbalanced bioassay data classification for drug discovery 

      Shah, Jeni Snehal (Dhirubhai Ambani Institute of Information and Communication Technology, 2018)
      All the methods developed for pattern recognition will show inferior performance if the dataset presented to it is imbalanced, i.e. if the samples belonging to one class are much more in number compared to the samples ...

    • Integrate active and meta-cognitive learning with extreme learning machine 

      Dave, Keval Narayanbhai (Dhirubhai Ambani Institute of Information and Communication Technology, 2017)
      "The extreme learning machine has become very popular due to its fast training and good generalization performance. The two considerations for extreme learning machine are fixed network structure and redundancy in training ...

    • Learning based approach for image compression 

      Kumar, Dheeraj (Dhirubhai Ambani Institute of Information and Communication Technology, 2015)
      Data compression is a process of storing same information with less data or space in computer memory. There are many image compression techniques that are available for storing images with less storage space. Minimizing ...

    • Learning cross domain relations using deep learning 

      Kotecha, Dhara (Dhirubhai Ambani Institute of Information and Communication Technology, 2018)
      The Generative Adversarial Networks (GAN) have achieved exemplary performance in generating realistic images. They also perform image to image translation and produce good results for the same. In this thesis, we explore ...

    • MEDICAL IMAGING USING MACHINE LEARNING TECHNIQUES 

      Sharma, Priyanka (Dhirubhai Ambani Institute of Information and Communication Technology, 2017)
      "We present an application of deep Convolutional Neural Networks (CNN) for theclassification of mammogram as normal, benign and malignant tumor. The images used in this study have been used from the mini-MIAS dataset of ...

    • Multi-class diagnosis of diabetic retinopathy using deep learning 

      Shrivastava, Udit (Dhirubhai Ambani Institute of Information and Communication Technology, 2018)
      Diabetic Retinopathy is the main cause of blindness in the modern world. As per studies, around 40-45% of people suffering from diabetes have DR in their later stages of life. All the forms of diabetic eye disease have ...

    • Multiresolution fusion of satellite images and super-resolution of hyper-spectral images 

      Shripat, Abhishek Kumar (Dhirubhai Ambani Institute of Information and Communication Technology, 2010)
      This thesis presents a model based approach for multi-resolution fusion of the satellite images. Given a high resolution panchromatic (Pan) image and a low spatial but high spectral resolution multi spectral (MS) image ...

    • Multiresolution fusion using compressive sensing and graph cuts 

      Harikumar, V. (Dhirubhai Ambani Institute of Information and Communication Technology, 2012)
      Multiresolution fusion refers to the enhancement of low spatial resolution (LR) of Multispectral (MS) images to that of Panchromatic (Pan ) image without compro- mising on the spectral details. Many of the present day ...