We use Mean Shift clustering in the latent space of an auto-encoder to have a better representation of the data and a more structured latent space. Instead of just using the mode of the distribution calculated using kernel ...

Previous studies have demonstrated that commonly studied (vanilla) touch-based continuous authentication systems (V-TCAS) are susceptible to population attack. This paper proposes a novel Generative Adversarial Network ...

Wireless devices, including mobile phones, laptops, autonomous driving, UAT, etc., generate an enormous amount of local data, which could be employed to train machine learning models for decision-making and improve prediction ...

This project focused on the deployment of a deep learning model for species categorization and retraining on the cloud using the YOLOv5x architecture. The goal was to create a web application that allows users to upload ...

Autonomous vehicles are becoming prevalent day-by-day, and with the advent of such technology comes its various safety risks and challenges. The primary objective is to improve road safety and mobility for all users. The ...

Locality sensitive hashing(LSH) is a hashing scheme that hashes objects into several buckets such that objects that are similar hashes into the same bucket and objects that are dissimilar hashes into different bucket with ...

We have researched on OpenSSL Random Number Generator (RNG) and Linux Random Number Generator and read about the vulnerabilities and loopholes in the RNGs which make it easier for the adversary to attack on the RNGs and ...

Blood cancer has emerged as a growing concern over the past decade, necessitating early detection for timely and effective treatment. Traditional methods of diagnosing blood cancers involve a series of pathological tests ...

In today’s world, it is no exaggeration that the environment and all its organisms face a threat due to environmental degradation of many kinds, and public transportation may be the answer to all the problems. It will help ...

Neural networks have emerged as a powerful tool in machine learning and deep learning, showcasing remarkable capabilities in image recognition, natural language processing, and autonomous decision-making tasks. However, ...