Results 91 to 100 of about 1,106,758 (269)

Version Spaces and Generalized Monotone Boolean Functions [PDF]

We consider generalized monotone functions f: X --> {0,1}defined for an arbitrary binary relationoperations research;ordinal classification;artificial intelligence;machine learning;partially defined Boolean ...
Bioch, J.C., Ibaraki, T.
core   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Deterministic Uncertainty Estimation for Multi-Modal Regression With Deep Neural Networks

IEEE Access
Prediction interval (PI) is a common method to represent predictive uncertainty in regression by deep neural networks. This paper proposes an extension of the prediction interval by using a union of disjoint intervals. Since previous PI methods assumed a
Jaehak Cho, Jae Myung Kim, Seungyub Han, Jungwoo Lee   +3 more
doaj   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

A novel model for expanding horizons in sign Language recognition

Scientific Reports
The American Sign Language Recognition Dataset is a pivotal resource for research in visual-gestural languages for American Sign Language and Sign-Language MNIST Dataset. The dataset contains over 64,000 images meticulously labeled with the corresponding
Esraa Hassan, Mahmoud Y. Shams, Tarek Abd El-Hafeez, Marwa Elseddik   +3 more
doaj   +1 more source

Alkali Ion‐Incorporated HfO2 Dielectrics for Reconfigurable Neuromorphic Computing

Advanced Functional Materials, EarlyView.
This work presents an indium gallium zinc oxide (IGZO) transistor with an alkali cation‐integrated hafnium dioxide (HfO2) dielectric exhibiting synaptic behavior via ion retention. The solution‐based film fabrication strategy overcomes the limitations of atomic layer deposition (ALD) and precursor coating, enabling the control of synaptic retention ...
Seung Yeon Ki, In Cheol Kwak, Seonkwon Kim, Jihyun Kim, Dong Gue Roe, Se‐Jin Kim, Joohoon Kang, Jeong Ho Cho   +7 more
wiley   +1 more source

Generating Artificial Data for Private Deep Learning

, 2019
In this paper, we propose generating artificial data that retain statistical properties of real data as the means of providing privacy with respect to the original dataset.
Faltings, Boi, Triastcyn, Aleksei
core  

Electron–Matter Interactions During Electron Beam Nanopatterning

Advanced Functional Materials, EarlyView.
This article reviews the electron–matter interactions important to nanopatterning with electron beam lithography (EBL). Electron–matter interactions, including secondary electron generation routes, polymer radiolysis, and electron beam induced charging, are discussed.
Camila Faccini de Lima, Prathiba Thamizhavel, Taylor J. Woehl   +2 more
wiley   +1 more source

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

The Application of Artificial Intelligence in Spectrum Management and the Analytics of Frequency Data Using Big Data Technology

IEEE Access
In order to support the development of more efficient spectrum management by using Big Data and Artificial Intelligence (AI), the authors study and propose a methodological framework that allows the application of Big Data and AI into spectrum management.
Rathapon Saruthirathanaworakun, Ngoc Thien Le, Truong Thanh Le, Wattanasak Srisiri, Surachai Chaitusaney, Pasu Kaewplung, Watit Benjapolakul   +6 more
doaj   +1 more source