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Results 91 to 100 of about 201,162 (313)

Rapeseed mapping using machine learning methods and Sentinel-1 time series coupled with growing degree-days information

Science of Remote Sensing
In light of recent escalations of geopolitical conflicts around the world, mapping rapeseed areas has garnered great interest given its importance to food security. Sentinel-1 (S1) SAR data was used for timely and regular rapeseed mapping. By coupling S1
Sami Najem +6 more
doaj +1 more source

Mapping Rice Paddy Based on Machine Learning with Sentinel-2 Multi-Temporal Data: Model Comparison and Transferability

Remote Sensing, 2020
Rice is an important agricultural crop in the Southwest Hilly Area, China, but there has been a lack of efficient and accurate monitoring methods in the region. Recently, convolutional neural networks (CNNs) have obtained considerable achievements in the
Weichun Zhang +4 more
doaj +1 more source

F1 Score Based Weighted Asynchronous Federated Learning

International Journal for Research in Applied Science and Engineering Technology
Abstract: The domain of federated learning has observed remarkable developments in recent years, enabling collaborative model training while preserving data privacy. This paper discusses several recent advancements in the field of federated learning, particularly in asynchronous and weighted federated learning.
Sneha Sree Yarlagadda, Sai Harshith Tule, Karthik Myada +2 more
openaire +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source

Evaluating parameters of each deep neural network model (%)—accuracy, precision, recall, F1 score, AUC score, sensitivity, and specificity.

, 2023
Evaluating parameters of each deep neural network model (%)—accuracy, precision, recall, F1 score, AUC score, sensitivity, and specificity.
Kiwon Na (14559789) +8 more
core +1 more source

AI‐Powered Framework for Evaluating Drug Efficacy for Three‐Dimensional In Vitro Cancer Models in Robot‐Assisted Production

Advanced Robotics Research, EarlyView.
An AI‐powered, robot‐assisted framework automatically produces, images, and analyzes 3D tumor spheroids to evaluate drug efficacy. Integrated modules handle spheroid formation, live/dead staining, brightfield imaging, and automated image analysis, including spheroid segmentation, viability and metrics to assess the drug treatment efficacy. The workflow
Dalia Mahdy +13 more
wiley +1 more source

An AI‐Enabled All‐In‐One Visual, Proximity, and Tactile Perception Multimodal Sensor

Advanced Robotics Research, EarlyView.
Targeting integrated multimodal perception of robots, an AI‐enabled all‐in‐one multimodal sensor is proposed. This sensor is capable of perceiving three types of modalities, including vision, proximity, and tactility. By toggling an ultraviolet light and adjusting the camera focus, it switches smoothly between multiple perceptual modalities, enabling ...
Menghao Pu +7 more
wiley +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello +2 more
wiley +1 more source

AUC, Recall (Rec), Specificity (Spe), Precision (Pre) and F1-score (F1) for each of the optimizers corresponding to the learning rates.

, 2022
AUC, Recall (Rec), Specificity (Spe), Precision (Pre) and F1-score (F1) for each of the optimizers corresponding to the learning rates.
Sidratul Montaha (13200394) +5 more
core +1 more source

machine learning
fos: computer and information sciences
f1-score

accuracy
deep learning
recall

precision
cnn
classification