Results 181 to 190 of about 2,392,377 (346)

Mean Absolute Error (MAE) results grouped by the connection (Call and SMS) and evaluation types.

Joel Jaskari (13165410), Chandreyee Roy (21492676), Fumiko Ogushi (6296846), Mikko Saukkoriipi (22822171), Jaakko Sahlsten (13165413), Kimmo Kaski (74278)   +5 more
openalex   +1 more source

Reducing Regression Time in Neural Network us-ing Nth Absolute Root Mean Error

, 2019
Siddhartha Dhar Choudhury, Shashank Pandey   +1 more
openalex   +1 more source

Evaluating the Accuracy of a Vision-Based Algorithm for Groundline Estimation in Trotting Horses Using Multiple Camera Angles. [PDF]

Vet Med Sci
Key K, Berg K, Kirkegaard J, Andresen KR, Hansen SS.   +4 more
europepmc   +1 more source

Quantifying Spin Defect Density in hBN via Raman and Photoluminescence Analysis

Advanced Functional Materials, EarlyView.
An all‐optical method is presented for quantifying the density of boron vacancy spin defects in hexagonal boron nitride (hBN). By correlating Raman and photoluminescence signals with irradiation fluence, defect‐induced Raman modes are identified and established an relationship linking optical signatures to absolute defect densities. This enables direct
Atanu Patra, Paul Konrad, Andreas Sperlich, Timur Biktagirov, Wolf Gero Schmidt, Lesley Spencer, Igor Aharonovich, Sven Höfling, Vladimir Dyakonov   +8 more
wiley   +1 more source

Refining estimation techniques for the Two-Sided Power Distribution: A data-sensitive perspective. [PDF]

PLoS One
Güral Y.
europepmc   +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

ANALISIS KEAKURATAN FORECAST RESIN ABS GRADE 500 322 MENGGUNAKAN PENDEKATAN MEAN ABSOLUTE PERCENTAGE ERROR (MAPE): STUDI KASUS INDUSTRI MANUFAKTUR PLASTIC COLORING DAN COMPOUNDING

, 2023
Dwi Irwati, Ade Nurul Hidayat
openalex   +2 more sources

Uncertainty Quantification in Molecular Machine Learning for Property Predictions under Data Shifts. [PDF]

J Chem Inf Model
Parrondo-Pizarro R, Lanini J, Rodríguez-Pérez R.   +2 more
europepmc   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

Offline evaluation of a predictive model : application to recommendation algorithms and to mean absolute percentage error.

, 2016
Arnaud De Myttenaere
openalex   +1 more source