In recent years, AI has undergone significant changes. Firstly, there is a growing recognition of the need to deploy inference models based on Deep Neural Networks (DNNs) on edge devices. Secondly, there is an increasing demand for low-energy inferencing ...

Spatiotemporal climatic variables like temperature, precipitation, humidity vary in a co-occurring fashion across different geographical zones. It is intuitive to believe that the co-occurrence is higher for signals sampled from nearby locations ...

In this work, we present a lightweight attention network to perform Time Series Classification on Edge devices. We evaluate the merit of our system on a Human Activity Recognition dataset and show the demonstration with the help of a Wearable device (...

In the following paper associated with a demonstration, we describe an in- house designed, developed and deployed versatile anomaly detection model called SCNet. The model is based on state-of-the-art deep learning techniques, and is targeted for ...

In this work, we perform Physics guided data synthesis. Proposed method uses seed data from the observed source state / domain for data generation of unobserved target state / domain. Our method adapts the variation of features with respect to the ...

Stress detection is important for ensuring overall mental well-being of an individual. Literature suggests several approaches for prediction or classification of stress. However, the performance of these approaches varies a lot across subjects and ...

The fourth industrial revolution, Industry 4.0, has brought internet, artificial intelligence (AI), and machine learning (ML) concepts into manufacturing. There is an  immediate need to understand the capabilities of AI and ML and how they can be ...

Differential dermal potentials is a non-invasive bio-potential signal acquired from the skin surface is a relatively new mode for human activity and behavior monitoring. Literature suggests acquiring differential dermal potentials from either hand or ...

Magnetic Resonance Imaging (MRI) has a long-standing acceptance as the de facto technology for obtaining high-resolution three-dimensional images of soft tissue pathologies of the knee. However, the volume and amount of information in MRI sequences ...

Intelligent continuous monitoring of an IoT system to identify the operational changes, encompassing both normal and abnormal scenarios, with drift in sensing device is a challenging problem. It demands capability of learning continuously with multiple ...

Fault diagnosis plays a vital role in ensuring the normal operation of the machine and safe production. In recent years, data-driven techniques have gained a lot of popularity for machine fault diagnosis. But most of these techniques assume the training ...

Deep Learning architectures used in computer vision, natural language and speech processing, unsupervised clustering, etc. have become highly complex and application-specific in recent times. Despite existing automated feature engineering techniques, ...

Model-based image reconstruction (MBIR) methods using convolutional neural networks (CNNs) as priors have demonstrated superior image quality and robustness compared to conventional methods. Studies have explored MBIR combined with supervised and ...

Electroencephalography (EEG) allows the study of the brain in humans with applications in areas of Psychology, Brain-Computer Interfaces, and Neuromarketing. The conventional systems limit the applications of EEG to lab environments, but recent ...

Data imbalance handling is important to have unbiased learning during model training of classification tasks. Synthetic minority over-sampling technique (SMOTE) is primarily used for data imbalance handling. Conventional SMOTE algorithm and its ...

The Photoplethysmogram (PPG) sensor is found in most smart wearables and fitness trackers to support the physical wellness monitoring of it's user. The popularity of this sensor has encouraged the exploration of it's use in other domains particularly in ...

According to World Health Organization (WHO) cardiovascular diseases (CVDs) are the number one cause of global deaths annually. More than 17 million people die each year from CVDs. To diagnose CVDs some clinical tests are required which are invasive and ...

The ability to assess cognitive load of an user in real time, is an integral part of effective human-computer interactions. Several approaches are used in literature for assessing cognitive load of an user in labs, however, assessment in real world ...

With the growing popularity of e-commerce, warehouse communication needs to operate in a dynamic environment with multiple robots in the system. Such multi-robot systems have many practical issues in reality. Among the major issues, end-to-end ...

Small form factor off-the shelf radar sensor nodes are being investigated for various privacy preserving non-contact sensing applications. This paper, presents a novel method, based on a system of spatially distributed radar setup(panel radar), for real ...