no code implementations • 24 Sep 2024 • Dibyasree Guha, Shyamali Mitra, Somenath Kuiry, Nibaran Das
Quantum neural networks are deemed suitable to replace classical neural networks in their ability to learn and scale up network models using quantum-exclusive phenomena like superposition and entanglement.
no code implementations • 31 Aug 2024 • Sayan Rakshit, Hmrishav Bandyopadhyay, Nibaran Das, Biplab Banerjee
In the second step, this pseudo source is adapted to the present target domain.
no code implementations • 16 Mar 2024 • Soumyajyoti Dey, Sukanta Chakraborty, Utso Guha Roy, Nibaran Das
Automation in medical imaging is quite challenging due to the unavailability of annotated datasets and the scarcity of domain experts.
no code implementations • 16 Mar 2024 • Anay Panja, Somenath Kuiry, Alaka Das, Mita Nasipuri, Nibaran Das
The typical Binary cross entropy(BCE) based U-shaped network only concentrates on the entire CT images without emphasizing on the affected regions, which results in hazy borders and low contrast in the projected output.
no code implementations • 16 Mar 2024 • Somenath Kuiry, Alaka Das, Mita Nasipuri, Nibaran Das
Researchers propose regularizing techniques, such as Label Smoothing (LS), which introduces soft labels for training data, making the classifier more regularized.
no code implementations • 16 Mar 2024 • Soumyajyoti Dey, Sukanta Chakraborty, Utso Guha Roy, Nibaran Das
In this paper, we have explored a fuzzy-based late fusion techniques for cytology image segmentation.
1 code implementation • 12 Nov 2022 • Avirup Dey, Nibaran Das, Mita Nasipuri
Historical Document Image Binarization is a well-known segmentation problem in image processing.
no code implementations • 21 Aug 2021 • Rohit Kundu, Hritam Basak, Akhil Koilada, Soham Chattopadhyay, Sukanta Chakraborty, Nibaran Das
Cervical cancer is the fourth most common category of cancer, affecting more than 500, 000 women annually, owing to the slow detection procedure.
no code implementations • 7 Aug 2021 • Hmrishav Bandyopadhyay, Shuvayan Ghosh Dastidar, Bisakh Mondal, Biplab Banerjee, Nibaran Das
Presently, Covid-19 is a serious threat to the world at large.
1 code implementation • 9 Jun 2021 • Hritam Basak, Rohit Kundu, Sukanta Chakraborty, Nibaran Das
A non-redundant, optimal feature subset is selected from this feature space using an evolutionary optimization algorithm, the Grey Wolf Optimizer, thus improving the classification performance.
Ranked #1 on
Image Classification
on SIPaKMeD
no code implementations • 23 Apr 2021 • Bodhisatwa Mandal, Swarnendu Ghosh, Teresa Gonçalves, Paulo Quaresma, Mita Nasipuri, Nibaran Das
Convolutional neural networks often generate multiple logits and use simple techniques like addition or averaging for loss computation.
no code implementations • 20 Feb 2021 • Shuvayan Ghosh Dastidar, Kalpita Dutta, Nibaran Das, Mahantapas Kundu, Mita Nasipuri
In this paper, we explore dark knowledge transfer approach using long short-term memory(LSTM) and CNN based assistant model and various deep neural networks as the teacher model, with a simple CNN based student network, in this domain of multi-script identification from natural scene text images.
no code implementations • 5 Feb 2021 • Md Osman Gani, Somenath Kuiry, Alaka Das, Mita Nasipuri, Nibaran Das
Moving outside the visible spectrum range, such as the thermal spectrum or the near-infrared (NIR) images, is much more beneficial in low visibility conditions, NIR images are very helpful for understanding the object's material quality.
no code implementations • 1 Feb 2021 • Hmrishav Bandyopadhyay, Tanmoy Dasgupta, Nibaran Das, Mita Nasipuri
With the advent of mobile and hand-held cameras, document images have found their way into almost every domain.
Ranked #2 on
SSIM
on DocUNet
no code implementations • 18 Aug 2020 • Bodhisatwa Mandal, Ritesh Sarkhel, Swarnendu Ghosh, Nibaran Das, Mita Nasipuri
To address this, we propose a novel two-phase dynamic routing protocol that computes agreements between neurons at various layers for micro and macro-level features, following a hierarchical learning paradigm.
1 code implementation • 20 Jul 2020 • Hmrishav Bandyopadhyay, Tanmoy Dasgupta, Nibaran Das, Mita Nasipuri
Capturing images of documents is one of the easiest and most used methods of recording them.
Ranked #1 on
SSIM
on DocUNet
1 code implementation • 27 Apr 2020 • Animesh Singh, Ritesh Sarkhel, Nibaran Das, Mahantapas Kundu, Mita Nasipuri
Finding local invariant patterns in handwrit-ten characters and/or digits for optical character recognition is a difficult task.
Optical Character Recognition
Optical Character Recognition (OCR)
no code implementations • 8 Apr 2020 • Arnab Banerjee, Nibaran Das, Mita Nasipuri
The ensemble approach clearly outperform all of the used deep learning networks.
no code implementations • 17 Mar 2020 • Shyamali Mitra, Nibaran Das, Soumyajyoti Dey, Sukanta Chakrabarty, Mita Nasipuri, Mrinal Kanti Naskar
Cytology is the branch of pathology which deals with the microscopic examination of cells for diagnosis of carcinoma or inflammatory conditions.
no code implementations • 15 Mar 2020 • Tanmoy Dasgupta, Nibaran Das, Mita Nasipuri
The present work demonstrates a fast and improved technique for dewarping nonlinearly warped document images.
no code implementations • 12 Mar 2020 • Soumyajyoti Dey, Soham Das, Swarnendu Ghosh, Shyamali Mitra, Sukanta Chakrabarty, Nibaran Das
One of the most challenging aspects of medical image analysis is the lack of a high quantity of annotated data.
no code implementations • 12 Mar 2020 • Somenath Kuiry, Nibaran Das, Alaka Das, Mita Nasipuri
In the literature, many fusion techniques are registered for the segmentation of images, but they primarily focus on observed output or belief score or probability score of the output classes.
1 code implementation • 28 Dec 2019 • Animesh Singh, Sandip Saha, Ritesh Sarkhel, Mahantapas Kundu, Mita Nasipuri, Nibaran Das
Deep neural network-based architectures give promising results in various domains including pattern recognition.
no code implementations • 13 Jul 2019 • Swarnendu Ghosh, Nibaran Das, Ishita Das, Ujjwal Maulik
This paper approaches these various deep learning techniques of image segmentation from an analytical perspective.
no code implementations • 13 Jul 2019 • Bodhisatwa Mandal, Swarnendu Ghosh, Ritesh Sarkhel, Nibaran Das, Mita Nasipuri
Capsule networks have gained a lot of popularity in short time due to its unique approach to model equivariant class specific properties as capsules from images.
no code implementations • IEEE Applied Signal Processing Conference 2018 (ASPCON 2018) 2019 • Bodhisatwa Mandal, Suvam Dubey, Swarnendu Ghosh, Ritesh Sarkhel, Nibaran Das
Convolutional neural networks(CNNs) has become one of the primary algorithms for various computer vision tasks.
no code implementations • 14 Mar 2018 • Aritra Das, Swarnendu Ghosh, Ritesh Sarkhel, Sandipan Choudhuri, Nibaran Das, Mita Nasipuri
Modern deep learning algorithms have triggered various image segmentation approaches.
no code implementations • 2 Feb 2018 • Saikat Roy, Nibaran Das, Mahantapas Kundu, Mita Nasipuri
In this work, a novel deep learning technique for the recognition of handwritten Bangla isolated compound character is presented and a new benchmark of recognition accuracy on the CMATERdb 3. 1. 3. 3 dataset is reported.
no code implementations • 5 Jan 2018 • Soumya Ukil, Swarnendu Ghosh, Sk Md Obaidullah, K. C. Santosh, Kaushik Roy, Nibaran Das
These are then used to train different CNNs to select features.
no code implementations • 2 May 2016 • Ritesh Sarkhel, Amit K Saha, Nibaran Das
A new region selection technique based on the idea of an enhanced Harmony Search methodology has been proposed here.
no code implementations • 22 Jan 2015 • Nibaran Das, Sandip Pramanik, Subhadip Basu, Punam Kumar Saha, Ram Sarkar, Mahantapas Kundu
In this work, 25 features are extracted based on different bays attributes of the convex hull of the digit patterns.
no code implementations • 22 Jan 2015 • Nibaran Das, Subhadip Basu, Ram Sarkar, Mahantapas Kundu, Mita Nasipuri, Dipak Kumar Basu
Appropriate feature set for representation of pattern classes is one of the most important aspects of handwritten character recognition.
no code implementations • 22 Jan 2015 • Ram Sarkar, Bibhash Sen, Nibaran Das, Subhadip Basu
The segmentation accuracy achieved by the current technique is 94. 8%.
no code implementations • 22 Jan 2015 • Nibaran Das, Subhadip Basu, Punam Kumar Saha, Ram Sarkar, Mahantapas Kundu, Mita Nasipuri
In the current work we have developed a two-pass approach where the first pass classifier performs a coarse classification, based on some global features of the input pattern by restricting the possibility of classification decisions within a group of classes, smaller than the number of classes considered initially.
no code implementations • 2 Oct 2014 • Nibaran Das, Sandip Pramanik, Subhadip Basu, Punam Kumar Saha, Ram Sarkar, Mahantapas Kundu, Mita Nasipuri
The current research aims to evaluate the performance of the convex hull based feature set, i. e. 125 features in all computed over different bays attributes of the convex hull of a pattern, for effective recognition of isolated handwritten Bangla basic characters and digits.