Optimal Squeeze Net with Deep Neural Network-Based Arial Image Classification Model in Unmanned Aerial Vehicles.
In present times, unmanned aerial vehicles (UAVs) are widely employed in several real time
applications due to their autonomous, inexpensive, and compact nature. Aerial image …
applications due to their autonomous, inexpensive, and compact nature. Aerial image …
Robust machine learning systems: Reliability and security for deep neural networks
Machine learning is commonly being used in almost all the areas that involve advanced
data analytics and intelligent control. From applications like Natural Language Processing …
data analytics and intelligent control. From applications like Natural Language Processing …
Advancements in microprocessor architecture for ubiquitous AI—An overview on history, evolution, and upcoming challenges in AI implementation
Artificial intelligence (AI) has successfully made its way into contemporary industrial sectors
such as automobiles, defense, industrial automation 4.0, healthcare technologies …
such as automobiles, defense, industrial automation 4.0, healthcare technologies …
NASCaps: A framework for neural architecture search to optimize the accuracy and hardware efficiency of convolutional capsule networks
Deep Neural Networks (DNNs) have made significant improvements to reach the desired
accuracy to be employed in a wide variety of Machine Learning (ML) applications. Recently …
accuracy to be employed in a wide variety of Machine Learning (ML) applications. Recently …
Hardware trojan design on neural networks
J Clements, Y Lao - 2019 IEEE International Symposium on …, 2019 - ieeexplore.ieee.org
Recent innovations and breakthroughs in deep neural networks have advanced or evolved
many industries as well as human daily life. To facilitate the deployment of these models to …
many industries as well as human daily life. To facilitate the deployment of these models to …
Exploring Computing Paradigms for Electric Vehicles: From Cloud to Edge Intelligence, Challenges and Future Directions
Electric vehicles are widely adopted globally as a sustainable mode of transportation. With
the increased availability of onboard computation and communication capabilities, vehicles …
the increased availability of onboard computation and communication capabilities, vehicles …
Spiker: an fpga-optimized hardware accelerator for spiking neural networks
A Carpegna, A Savino… - 2022 IEEE Computer …, 2022 - ieeexplore.ieee.org
Spiking Neural Networks (SNN) are an emerging type of biologically plausible and efficient
Artificial Neural Network (ANN). This work presents the development of a hardware …
Artificial Neural Network (ANN). This work presents the development of a hardware …
Throughput/area optimised pipelined architecture for elliptic curve crypto processor
A pipelined architecture is proposed in this work to speed up the point multiplication in
elliptic curve cryptography (ECC). This is achieved, at first; by pipelining the arithmetic unit to …
elliptic curve cryptography (ECC). This is achieved, at first; by pipelining the arithmetic unit to …
A review of emerging technologies for IoT-based smart cities
Smart cities can be complemented by fusing various components and incorporating recent
emerging technologies. IoT communications are crucial to smart city operations, which are …
emerging technologies. IoT communications are crucial to smart city operations, which are …
Energy-efficient convolution architecture based on rescheduled dataflow
This paper presents a rescheduled dataflow of convolution and its hardware architecture
that can enhance energy efficiency. For convolution involving a large amount of …
that can enhance energy efficiency. For convolution involving a large amount of …