Results 81 to 90 of about 99,068 (260)

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

Passenger Screening using Deep Learning and Artificial Neural Networks

International Journal of Engineering and Management Research, 2019
In this research, we have to detect the contrabands hidden in the human body’s scanned images at airport security machines using segmentation and classification. Present algorithm of security scanning machines at the airports of USA are producing high rate of false negatives which in cases lead to engage in a secondary, manual screening process that ...
, Sarthak Arora, , Ankit Singh Rathore, , Saurabh Gautam   +2 more
openaire   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

1‐D Collocated Dual‐Gradient Sensory Fibers for Comprehensive Sensing and Decoding of Complex Human Motion and Physiology

Advanced Materials, EarlyView.
Coupled materials design enables a monolithic fiber that integrates complementary sensing regimes into a single wearable strand. By preserving informative signal features across subtle physiological deformation, large body motion, and mixed mechanical inputs, the dual‐gradient architecture generates synchronized, less redundant outputs that improve ...
Yunheum Lee, Sungha Jeon, Min Kim, Joonhee Won, Jinwook Yeo, Kyunghyun Jo, Soyeon Lee, Kieun Park, Yechan Yang, Chul Kim, Gun‐Hee Lee, Seunghwa Ryu, Sungho Jo, Seongjun Park   +13 more
wiley   +1 more source

Bio-Inspired Neural Network Dynamics-Aware Reinforcement Learning for Spiking Neural Network

Biomimetics
Artificial Intelligence (AI) has seen rapid advancements in recent times, finding applications across various sectors and achieving notable successes. However, current AI models based on Deep Convolutional Neural Networks (DNNs) face numerous challenges,
Yu Zheng, Jingfeng Xue, Junhan Yang, Yanjun Zhang   +3 more
doaj   +1 more source

Deep Learning Methods Used in Precision Agriculture [PDF]

BIO Web of Conferences
Precision agriculture is an important field that aims to optimize crop yields and quality, and it is crucial for ensuring food security and sustainability.
Wang Yuchu
doaj   +1 more source

Hydrophobic MFI‐Type Zeolites via Alkali‐Cation‐Induced Defect Healing: Implications for Adsorbent and Catalyst Design

Advanced Materials, EarlyView.
Sub‐stoichiometric amounts of Na+ or K+ enhance defect healing during Silicalite‐1 (MFI) and TS‐1 calcination by promoting Si–O–Si annealing and healing framework vacancies. The resulting defect‐free zeolites are more hydrophobic and show improved butanol/water separation and improved activity and selectivity in the epoxidation of 1‐hexene, offering a ...
Christos Kanteler, Pau Ferri, Francisco Javier Escobar‐Bedia, Álvaro Mayoral, Alejandro Vidal‐Moya, Richard Kendra, Chen Lei, Miguel Palomino, Fernando Rey, Lukáš Grajciar, Christopher James Heard, Pedro Serna, Mercedes Boronat, Cristina Martínez, Manuel Moliner   +14 more
wiley   +1 more source

Artificial Intelligence in Ship Trajectory Prediction

Journal of Marine Science and Engineering
Maritime traffic is increasing more and more, creating more complex navigation environments for ships. Ship trajectory prediction based on historical AIS data is a vital method of reducing navigation risks and enhancing the efficiency of maritime traffic
Jinqiang Bi, Hongen Cheng, Wenjia Zhang, Kexin Bao, Peiren Wang   +4 more
doaj   +1 more source

Review of Graph Neural Networks [PDF]

Jisuanji kexue
With the rapid development of artificial intelligence,deep learning has achieved great success in data that can be represented in Euclidean spaces,such as images,text,and speech.However,it has been difficult to apply deep learning to non-Eucli-dean ...
HOU Lei, LIU Jinhuan, YU Xu, DU Junwei
doaj   +1 more source

Noise‐Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency‐Selective Time‐Series Signal Encoding

Advanced Materials, EarlyView.
Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim, Seoeun Jang, Hakseung Rhee, Min Gu Lee, Daehee Kim, Taewook Go, Woon Hyung Cheong, Hanchan Song, Kyung Min Kim   +8 more
wiley   +1 more source