On-device ML is increasingly used in different applications. It brings convenience to offline
tasks and avoids sending user-private data through the network. On-device ML models are …

Deep Learning is one of the most popular computer science techniques, with applications in
natural language processing, image processing, pattern identification, and various other …

Machine learning (ML) represents one of the main pillars of the current digital era,
specifically in modern real-world applications. The Internet of Things (IoT) technology is …

In the current scenario of the world, most of the learning has been shifted to e-learning
modes like online classes. In a live class, a teacher is able to constantly monitor the students …

In biometric applications, deep neural networks have presented significant improvements.
However, when presenting carefully designed input training data known as adversarial …

With the gaining popularity of Artificial intelligence and its adoption by organizations in their
day-to-day business operations, it is becoming increasingly important to defend machine …

Sažetak Globally, cardiovascular diseases stand as the primary cause of mortality. In
response to the imperative to enhance operational efficiency and reduce expenses …

Deep neural networks have shown significant progress in biometric applications. Deep
learning networks are particularly vulnerable to Adversarial examples where adversarial …

Despite being known for their robust performance in the biometrics domain, Deep
Convolutional Neural Networks always face a high risk of being fooled by precisely …

In Biometric traits, Iris plays an important role in person authentication because it has
complex structure and the patterns have unique and rich features as compared to other traits …