Results 31 to 40 of about 7,279,238 (253)

EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search

CoRR, 2021
In hardware-aware Differentiable Neural Architecture Search (DNAS), it is challenging to compute gradients of hardware metrics to perform architecture search. Existing works rely on linear approximations with limited support to customized hardware accelerators. In this work, we propose End-to-end Hardware-aware DNAS (EH-DNAS), a seamless integration of
Qian Jiang, Xiaofan Zhang 0001, Deming Chen, Minh N. Do, Raymond A. Yeh   +4 more
openaire   +3 more sources

Efficient Resource-Aware Neural Architecture Search with a Neuro-Symbolic Approach [PDF]

, 2023
Hardware-aware Neural Architectural Search (NAS) is gaining momentum to enable the deployment of deep learning on edge devices with limited computing capabilities.
Alice Bizzarri, Elena Bellodi, Michele Fraccaroli, Davide Bertozzi, Riccardo Zese, Michele Favalli   +5 more
core   +1 more source

A systematic literature review of lightweight YOLO models for object detection [PDF]

PeerJ Computer Science
Object detection is a core task in computer vision, and the You Only Look Once (YOLO) family remains a preferred choice for real-time applications. With increasing demand to deploy detectors on resource-constrained devices, many researchers have proposed
Lili Wang, Haoliang Wang, Sukumar Letchmunan, Renhao Xiao, Omed Hassan Ahmed, Zhe Liu   +5 more
doaj   +2 more sources

Array-Aware Neural Architecture Search [PDF]

, 2020
Convolutional Neural Networks (CNNs) have exceeded human accuracy in many Computer Vision tasks, such as Image Classification, Object Detection, Image Segmentation, etc.
Chitty-Venkata, Krishna, Somani, Arun
core  

Re-Thinking Electronic Circuit Design Through Emerging Reconfigurable Field Effect Transistors. [PDF]

Adv Sci (Weinh)
Graphical illustration of reconfigurable field effect transistor (RFET) operation modes, including n‐type, p‐type, and ambipolar transport, as well as their areas of application discussed in this review: digital circuit design, analog circuit design, post‐Shannon computing, and sensing. ABSTRACT Reconfigurable field‐effect transistors, short RFETs, are
Trommer J, Martinez JP, He Y, Galderisi G, Pingen K, Oliveros-Mata ES, Tellis L, Cakirlar C, Beyer C, Sapui B, Knoch J, Hofmann K, Carrara S, Cantatore E, Lemme MC, O'Connor I, Kumar A, Heinzig A, Mikolajick T, Weber WM.   +19 more
europepmc   +2 more sources

Landscape Analysis for Multi-Objective Hardware-Aware Neural Architecture Search in Earth Observation Applications [PDF]

, 2023
Recent advancements in the field of AutoML, particularly in Neural Architecture Search (NAS), offer exciting possibilities for both researchers and industry practitioners by automating the design of neural networks. While many NAS studies have focused
Demir, Emre
core  

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Harmonic-NAS: Hardware-Aware Multimodal Neural Architecture Search on Resource-constrained Devices

CoRR, 2023
The recent surge of interest surrounding Multimodal Neural Networks (MM-NN) is attributed to their ability to effectively process and integrate multiscale information from diverse data sources. MM-NNs extract and fuse features from multiple modalities using adequate unimodal backbones and specific fusion networks.
Mohamed Imed Eddine Ghebriout, Halima Bouzidi, Smaïl Niar, Hamza Ouarnoughi   +3 more
openaire   +3 more sources

Hardware-aware design, search, and optimization of deep neural networks [PDF]

, 2023
Deep Learning has achieved remarkable progress in the last decade due to its powerful automatic representation capability for a variety of tasks, such as Image Recognition, Speech Recognition, and Machine Translation.
Chitty-Venkata, Sai Subra
core   +1 more source

Advances in Bio‐Integrated Edge Computing Systems for Smart and Connected Health

Advanced Materials, EarlyView.
This review explores advances in bio‐integrated edge computing for healthcare, focusing on co‐designing computing, sensing, and energy strategies to overcome integration and power challenges for optimized, decentralized operation. ABSTRACT Recent advances in bio‐integrated healthcare technologies have enabled continuous, high‐resolution monitoring and ...
Gyuwon Kim, Seungwon Yoo, Tae Woog Kang, Yunuo Huang, Woon‐Hong Yeo   +4 more
wiley   +1 more source