Advances in Machine Learning (ML) have led to its adoption as an integral component in many applications, including banking, medical diagnosis, and driverless cars. To further broaden the use of ML models, cloud-based services offered by Microsoft, Amazon, Google, and others have developed ML-as-a-service tools as black-box systems. However, ML classifiers are vulnerable to adversarial examples...

This paper investigates strategies that defend against adversarial-example attacks on image-classification systems by transforming the inputs before feeding them to the system. Specifically, we study applying image transformations such as bit-depth reduction, JPEG compression, total variance minimization, and image quilting before feeding the image to a convolutional network classifier. Our exp...

This paper investigates strategies that defend against adversarial-example attacks on image-classification systems by transforming the inputs before feeding them to the system. Specifically, we study applying image transformations such as bit-depth reduction, JPEG compression, total variance minimization, and image quilting before feeding the image to a convolutional network classifier. Our exp...

During last couple of decades, a lot efforts had been devoted by researchers in exploring gene disease relationships using Genome Wide Association studies. These among gene-disease can showcase new dimensions correlations at genetic level which may lead to reveal similarity. help prevention, diagnosis and treatment level. Also proper understanding between genes will better explanation complex f...

Few-shot classification (FSC) aims at classifying query samples into correct classes given only a few labelled samples. Prototypical Classifier (PC) can be chosen to an ideal classifier for settling this problem, as it has good properties of low-capacity and parameter-free. However, the mean-based prototypes suffer from issue deviating its ground-truth centre. In order solve such problem protot...

There are so many social networking sites available. Tweets have evolved into a crucial tool for gathering people's thoughts, ideas, behaviours and sentiments surrounding particular entities. One of the most intriguing subjects in this context is analyzing sentiment tweets using natural language processing (NLP). Although several methods been created, accuracy effectiveness those analysis yet t...

Combining classifiers has proved to be an effective solution to several classification problems in pattern recognition. In this paper we use classifier combination methods for the classification of natural images. In the image classification, it is often beneficial to consider each feature type separately, and combine the classification results in the final classifier. We present a classifier c...