Results 61 to 70 of about 73,468 (309)

The effect of image resolution on convolutional neural networks in breast ultrasound

Heliyon, 2023
Purpose: The objective of this research was to investigate the efficacy of various parameter combinations of Convolutional Neural Networks (CNNs) models, namely MobileNet and DenseNet121, and different input image resolutions (REZs) ranging from 64×64 to
Shuzhen Tang, Chen Jing, Yitao Jiang, Keen Yang, Zhibin Huang, Huaiyu Wu, Chen Cui, Siyuan Shi, Xiuqin Ye, Hongtian Tian, Di Song, Jinfeng Xu, Fajin Dong   +12 more
doaj   +1 more source

Performance Enhancement of Tin Chloride‐Incorporated Ferroelectric Polymer‐Based Artificial Synapse for Hardware Neural Networks

Advanced Functional Materials, EarlyView.
This paper proposes a highly efficient ferroelectric artificial synapse device based on an oxide semiconductor and SnCl2‐inserted P(VDF‐TrFE) gate dielectric layer. This FeFET significantly improved the synaptic performance due to the ion‐dipole interaction.
Hyun‐Soo Kim, Hyunkyu Lee, Yeonho Choi, Won Young Jang, Hyungmin Kim, Krishna Moorthy Ponnusamy, Hongseung Lee, Jaewook Yoo, Ji Ye Lee, S. Chandramohan, Seongin Hong, Hagyoul Bae, Hyeon‐Sik Jang, Sang Yeol Lee, Keun Heo   +14 more
wiley   +1 more source

A New Deep Convolutional Network for Effective Hyperspectral Unmixing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Hyperspectral unmixing extracts pure spectral constituents (endmembers) and their corresponding abundance fractions from remotely sensed scenes. Most traditional hyperspectral unmixing methods require the results of other endmember extraction algorithms ...
Xuanwen Tao, Mercedes E. Paoletti, Lirong Han, Zhaoyue Wu, Peng Ren, Javier Plaza, Antonio Plaza, Juan M. Haut   +7 more
doaj   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Directly Connected Convolutional Neural Networks [PDF]

, 2018
Convolutional neural networks (CNNs) have better performance in feature extraction and classification. Most of the applications are based on a traditional structure of CNNs.
Zhanji Gui, Jun Ou, Shuqing Li, Qingxiu Wu   +3 more
core   +1 more source

การวิเคราะห์การมีส่วนร่วมของนักเรียนในห้องเรียนออนไลน์ โดยใช้ Convolutional Neural Networks (CNN)

วารสารงานวิจัยและพัฒนาเชิงประยุกต์ โดยสมาคม ECTI, 2023
การระบาดของเชื้อไวรัสโคโรนา (COVID-19) ส่งผลกระทบในภาคการศึกษา เช่น การเรียนจาก ห้องเรียนปกติสู่ห้องเรียนออนไลน์ ทำให้การติดตามการมีส่วนร่วมในห้องเรียนออนไลน์เป็นไปด้วยความ ยากลำบาก นอกจากจะส่งผลต่อประสิทธิภาพของผู้เรียนแล้ว กรณีที่ร้ายแรงที่สุดที่อาจจะเกิดขึ้นคือการ หลุดจากการศึกษาของผู้เรียน เพื่อให้ผู้สอนได้ทราบถึงการมีส่วนร่วมของผู้เรียนและสามารถปรั
openaire   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

ANALYSING MARINE ANIMALS CHARACTERISTICS USING CONVOLUTIONAL NEURAL NETWORKS [PDF]

, 2019
The thesis explores the efficacy of convolutional neural network(CNNs) to categorize lobster images for improving lobster grading and traceability. Traceability ensures that lobsters are traceable to a sustainable source.
Sachdeva, Parmeet Singh
core  

NASB: Neural Architecture Search for Binary Convolutional Neural Networks [PDF]

, 2020
Binary Convolutional Neural Networks (CNNs) have significantly reduced the number of arithmetic operations and the size of memory storage needed for CNNs, which makes their deployment on mobile and embedded systems more feasible.
Zhu, B. (author), Baozhou Zhu, Zaid Al-Ars, Al-Ars, Z., Zhu, B., Hofstee, H.P. (author), Hofstee, H.P., H. Peter Hofstee, Al-Ars, Z. (author)   +8 more
core   +1 more source