Overview Different vectorial and / or (dis)similarity representations can be produced for a given data. These distinct representations or data generating models have typically been used individually, in single classifiers or single clustering algorithms, or simultaneously, as in classifier combination techniques or cluster ensemble methods, depending, respectively, on whether working under a su...

In this project we use supervised learning to develop a classifier for stellar lightcurves to detect whether they demonstrate the existence of exosolar planets. We use various features selection methods; in particular we will be using dynamic time warping to measure the similarity between two temporal sequences.

Shaded similarity matrix has long been used in visual cluster analysis. This paper investigates how it can be used in classification visualization. We focus on two popular classification methods: nearest neighbor and decision tree. Ensemble classifier visualization is also presented for handling large data sets.

This paper describes the Sagan system in the context of the Sixth Pascal Recognizing Textual Entailment (RTE6) and the RTE task within a Corpus. The system employs a Support Vector Machine classifier which uses semantic similarity metrics to sentence level using only WordNet as source of knowledge, and co-reference analysis. Additionally, we proposed a baseline to the Novelty Detection subtask.

An one-line image database search method, which utilizes the boosted-shape feature similarities, is proposed. Salient common feature informations provided by the relevance feedback or multi-instance query are boosted for improving retrieval results. Weak classifiers are successively refined to yield a final strong classifier. The similarity between two shape samples was measured in statistic sp...

In this paper, we propose a new text recognition model based on measuring the visual similarity of text and predicting the content of the unlabeled texts. First a Siamese network is trained with deep supervision on a labeled training dataset. This network projects texts into a similarity manifold. The Deeply Supervised Siamese network learns visual similarity of texts. Then a K-nearest neighbor...

Interpretable semantic textual similarity (iSTS) task adds a crucial explanatory layer to pairwise sentence similarity. We address various components of this task: chunk level semantic alignment along with assignment of similarity type and score for aligned chunks with a novel system presented in this paper. We propose an algorithm, iMATCH, for the alignment of multiple non-contiguous chunks ba...

This paper evaluates strategies for atlas selection in atlas-based segmentation of three-dimensional biomedical images. Segmentation by intensity-based nonrigid registration to atlas images is applied to confocal microscopy images acquired from the brains of 20 bees. This paper evaluates and compares four different approaches for atlas image selection: registration to an individual atlas image ...

Optical Character Recognition (OCR) is one of the important fields in image processing and pattern recognition domain. Handwritten character recognition has always been a challenging task. Only a little work can be traced towards the recognition of handwritten characters for the south Indian languages. Kannada is one such south Indian language which is also one of the official language of India...

Machine learning (ML) based classifiers are vulnerable to evasion attacks, as shown by recent attacks. However, there is a lack of systematic study attacks on ML-based anti-phishing detection. In this study, we show that not only effective practical classifiers, but can also be efficiently launched without destructing the functionalities and appearance. For purpose, propose three mutation-based...