Edge-AI-driven framework with efficient mobile network design for facial expression recognition

Y Wu, L Zhang, Z Gu, H Lu, S Wan - ACM Transactions on Embedded …, 2023 - dl.acm.org
Facial Expression Recognition (FER) in the wild poses significant challenges due to realistic
occlusions, illumination, scale, and head pose variations of the facial images. In this article …

Dyno: Dynamic onloading of deep neural networks from cloud to device

M Almeida, S Laskaridis, SI Venieris… - ACM Transactions on …, 2022 - dl.acm.org
Recently, there has been an explosive growth of mobile and embedded applications using
convolutional neural networks (CNNs). To alleviate their excessive computational demands …

Implementation of generative adversarial networks in mobile applications for image data enhancement

O Striuk, Y Kondratenko - Journal of Mobile Multimedia, 2023 - journals.riverpublishers.com
This article aims to explore and research GANs as a tool for mobile devices that can
generate high-resolution images from low-resolution samples and reduce blurring. In …

A general hardware and software Co-design framework for energy-efficient edge AI

NK Jayakodi, JR Doppa… - 2021 IEEE/ACM …, 2021 - ieeexplore.ieee.org
A huge number of edge applications including self-driving cars, mobile health, robotics, and
augmented reality/virtual reality are enabled by deep neural networks (DNNs). Currently …

Real-time Blood Pressure Prediction on Wearables with Edge-Based DNNs: A Co-Design Approach

T Joseph, B TS - ACM Transactions on Design Automation of Electronic …, 2024 - dl.acm.org
This paper presents the hardware realization of a real-time blood pressure (BP) prediction
model for wearable devices, utilizing long short-term memory (LSTM) deep neural networks …

ZeroD-fender: A Resource-aware IoT Malware Detection Engine via Fine-grained Side-channel Analysis

Z Li, D Zhao - ACM Transactions on Design Automation of Electronic …, 2024 - dl.acm.org
In early 2023, cyberattacks experienced a significant rise due to unknown (zero-day)
malware targeting Internet of Things (IoT) devices. To tackle the challenge of zero-day …

Intelligence Inference on IoT Devices

Q Zhang, Y Li, D Zhang, I Murturi, VC Pujol… - Learning Techniques for …, 2023 - Springer
With the rapid advancement of artificial intelligence (AI), the proliferation of deep neural
networks (DNNs) has ushered in a transformative era, revolutionizing modern lifestyles and …

Adaptive Experimental Design for Optimizing Combinatorial Structures

A Deshwal - 2024 - search.proquest.com
Many real-world scientific and engineering problems can be formulated as instances of goal-
driven adaptive experimental design, wherein candidate experiments are chosen …

[BOOK][B] An Adaptive Framework for Energy-Efficient Edge AI: From Classification to Synthesis of Images and 3D Shapes

KJ Nitthilan - 2022 - search.proquest.com
A large number of real-time artificial intelligence (AI) applications including robotics, self-
driving cars, smart health and augmented (AR)/virtual reality (VR) are enhanced/boosted by …

An Adaptive Framework for Energy-Efficient Edge AI: from Classification to Synthesis of Images and 3D Shapes

NK Jayakodi - rex.libraries.wsu.edu
A large number of real-time artificial intelligence (AI) applications including robotics, self-
driving cars, smart health and augmented (AR)/virtual reality (VR) are enhanced/boosted by …