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An improved landmark-driven and spatial–channel attentive convolutional neural network for fashion clothes classification

Shajini, M.; Ramanan, A. (University of Jaffna, 2020)

Fashion clothes classification encompasses spotting and identifying items of clothing in an image. This area of research has involved using deep neural networks to make an impact in the field of social media, e-commerce ...

A blockchain-based database management system

Tharani, J.M.; Tharmakulasingam, M.; Muthukkumarasamy, V. (University of Jaffna, 2020)

The software and hardware applications are clearly on the way of becoming an integral tool of business, communication and popular culture in many parts of the world. People are interacting with the environ ment via the ...

Subcategory classifiers for multiple-instance learning and its application to retinal nerve fiber layer visibility classification

Siyamalan, M. (2017)

We propose a novel multiple-instance learning (MIL) method to assess the visibility (visible/not visible) of the retinal nerve fiber layer (RNFL) in fundus camera images. Using only image-level labels, our approach learns to ...

Structure prediction for gland segmentation with hand-crafted and deep convolutional features

Siyamalan, M. (2018)

We present a novel method to segment instances of glandular structures from colon histopathology images. We use a structure learning approach which represents local spatial configurations of class labels, capturing structural ...

Loss functions for optimizing Kappa as the evaluation measure for classifying diabetic retinopathy and prostate cancer images

Nirthika, R.; Siyamalan, M.; Ramanan, A. (2020)

Quadratic Weighted Kappa (QWK) is a statistic to measure the agreement between two annotators. QWK has been widely used as the evaluation measure for various medical imaging problems, where, the class labels have a natural ...

Convolutional neural network and feature encoding for predicting the outcome of cricket matches

Siyamalan, M.; Kausik, M. (2019)

This paper proposes two novel approaches for predicting the outcome of cricket matches by modelling the team performance based on the performances of it’s players in other matches. Our first approach is based on feature encoding, ...

Comparative analysis of different features and encoding methods for rice image classification

Nirmalan, V.E.; Nawarathna, R.D.; Siyamalan, M. (2018)

Rice is the most widely consumed staple food in Sri Lanka. In this paper, we present a comparative study of different features (SIFT, Multi-resolution Local Patterns, Local Color Histograms, and Random Projections) and ...

Biomarker localization by combining CNN Classifier and generative adversarial network

Zhang, R.; Shuhan, T.; Ruixuan, W.; Siyamalan, M.; Chen, J.; Lin, H.; Zheng, W.S. (Springer Nature Switzerland, 2019)

Sequential Input Space Carving for visual codebook design

Barathy, M. (BMVA, 2013-10-04)

In well-known framework for visual scene recognition literature, clustering to construct a visual codebook is an important step, and is usually achieved by k-means clustering. This is known to be computational and performance ...

Compact Codebook Design for Visual Scene Recognition by Sequential Input Space Carving

Barathy, G.; Mahesan, S.; Pinidiyaarachchi, U.A.J. (IEEE, 2013-09-25)

We present a novel approach to the design of codebooks in patch-based, bag-of-feature visual scene recognition problems. The Sequential Input Space Carving (SISC) approach we present achieves compact codebooks in a fraction ...

Content Based Image Retrieval: An overview of structure of the image and image database

Barathy, G.; Mahesan, S.; Pinidiyaarachchi, U.A.J. (SLIIT, 2011-01-27)

There are a number of challenging problems in Content Based Image Retrieval (CBIR) particularly on structure of the image and image database. Separating an image into its constituent parts is a major task in this area. In ...

A Morphological and Gradient based Approach to Classify Plant Leaves Using Support Vector Machines

Kobikrishna, P.; Ramanan, A. (iPURSE, 2015-11-06)

Plants are an important resource for human well-being. Plant recognition is very essential in agriculture for the management of plant types whereas botanists can use this application for medicinal purposes. Leaves of ...

Online Multi-Person Tracking-by-Detection Method Using ACF and Particle Filter

Kokul, T.; Ramanan, A.; Pinidiyaarachchi, U.A.J. (IEEE, 2015-12-12)

Automatically detecting and tracking multiple persons in videos is one of the main research interest in computer vision based applications. This paper presents a tracking-by-detection approach for tracking people in dynamic ...

A Pre-processing Method for Printed Tamil Documents: Skew Correction and Textual Classification

Ramanan, M.; Ramanan, A.; Charles Eugene, Y. (IEEE, 2015-12-12)

An Optical character recognition (OCR) consists of the phases: preprocessing and segmentation, feature extraction, classification and post-processing. This paper focuses on pre-processing and segmentation tasks which plays ...

Creating Compact and Discriminative Visual Vocabularies using Visual Bits

Kirishanthy, T.; Ramanan, A. (IEEE, 2015-11-24)

In a patch-based object recognition system the key role of a visual vocabulary is to provide a way to map the low-level features into a fixed-length vector in histogram space to which standard classifiers can be directly ...

Front-view Car Detection using Vocabulary Voting and Mean-Shift Search

Sotheeswaran, S.; Ramanan, A. (IEEE, 2015-08-25)

Vehicle detection has received much attention over the recent years. In this paper we mainly address on the detection of cars in front-view static images and focus on local features that describe structural characteristics ...

A Hybrid Decision Tree for Printed Tamil Character Recognition Using SVMs

Ramanan, M.; Ramanan, A.; Charles Eugene Y. (IEEE, 2015-08-25)

Optical character recognition (OCR) is one of the important research areas in image processing and pattern recognition. OCR for printed Tamil text is considered as a challenging problem due to the large number of (i.e., ...

A Classifier-Free Codebook-based Image Classification of Vehicle Logos

Sotheeswaran, S.; Ramanan, A. (IEEE, 2014-12-15)

Logo identification and classification have received considerable attention from both the machine learning and computer vision communities. Vehicle logo recognition (VLR) is used to recognise accurately the manufacturer ...

A Performance Comparison and Post-processing Error Correction Technique to OCRs for Printed Tamil Texts

Ramanan, M.; Ramanan, A.; Charles Eugene, Y. (IEEE, 2014-12-15)

Optical Character Recognition (OCR) deals with automated recognition of characters that are in the format of digital image. OCR refers to the process by which scanned images are electronically processed and converted to ...

One-Pass Clustering Superpixels

Kesavan, Y.; Ramanan, A. (IEEE, 2014-12-22)

A superpixel is an image patch which is better aligned with intensity edges than a rectangular patch. Superpixels are perceptually consistent units which carry more information than pixels and adhere well to image boundaries. ...

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