云南高校图书馆联盟文献共享服务平台- Artificial Intelligence in Agriculture

《Artificial Intelligence in Agriculture》: 作品数：160被引量：330H指数：9; 导出分析报告; 主办单位：中国科技出版传媒股份有限公司; 最新期次：2024年4期更多>>; 发文主题：MACHINE_LEARNINGAGRICULTURECOMPUTER_VISIONREVIEWSMART更多>>; 发文领域：自动化与计算机技术农业科学经济管理电子电信更多>>; 发文基金：国家自然科学基金中国博士后科学基金国家科技支撑计划国家高技术研究发展计划更多>>

A review of external quality inspection for fruit grading using CNN models: 《Artificial Intelligence in Agriculture》2024年第4期1-20,共20页Luis E.Chuquimarca Boris X.Vintimilla Sergio A.Velastin; supported by the ESPOL-CIDIS-11-2022 project.; This article reviews the state of the art of recent CNN models used for external quality inspection of fruits,considering parameters such as color,shape,size,and defects,used to categorize fruits according to internat...; 关键词：External-quality INSPECTION FRUITS GRADING CNN

Automatic location and recognition of horse freezing brand using rotational YOLOv5 deep learning network: 《Artificial Intelligence in Agriculture》2024年第4期21-30,共10页Zhixin Hua Yitao jiao Tianyu Zhang Zheng Wang Yuying Shang Huaibo Son; supported by the National Key Research and Development Program of China (Grant No.2023YFD1301801);National Na-ural Science Foundation of China (No.32272931).; Individual livestock identification is of great importance to precision livestock farming.Liquid nitrogen freezing labeled horse brand is an effective way for livestock individual identification.Along with various tec...; 关键词：Horse brand Rotating target detection YOLOv5 CSL Number recognition

Estimating TYLCV resistance level using RGBD sensors in production greenhouse conditions: 《Artificial Intelligence in Agriculture》2024年第4期31-42,共12页Dorin Shmaryahu Rotem Lev Lehman Ezri Peleg Guy Shani; supported by the ISF fund,grants no.964/22 and 120/18;by the Helmsley Charitable Trust through the ABC fund。; Automated phenotyping is the task of automatically measuring plant attributes to help farmers and breeders in developing and growing strong robust plants.An automated tool for early illness detection can accelerate th...; 关键词：PHENOTYPING TYLCV TOMATO Deep learning RGB-D

Utility-based regression and meta-learning techniques for modeling actual ET:Comparison to(METRIC-EEFLUX)model: 《Artificial Intelligence in Agriculture》2024年第4期43-55,共13页Fatima K.Abu Salem Sara Awad Yasmine Hamdar Samer Kharroubi Hadi Jaafar; Estimating actual evapotranspiration(ET.)is crucial for water resource management,yet existing methods face limitations.Traditional approaches,including eddy covariance and remote sensing-based energy balance methods,...; 关键词：EVAPOTRANSPIRATION Machine learning Artificial intelligence EEFlux

Development of a cutting-edge ensemble pipeline for rapid and accurate diagnosis of plant leaf diseases: 《Artificial Intelligence in Agriculture》2024年第4期56-72,共17页S.M.Nuruzzaman Nobel Maharin Afroj Md Mohsin Kabir M.F.Mridha; Selecting techniques is a crucial aspect of disease detection analysis,particularly in the convergence of computer vision and agricultural technology.Maintaining crop disease detection in a timely and accurate manner ...; 关键词：Leaf disease Transfer learning GradCam Saliency map Computer vision SUSTAINABILITY AGRICULTURE

Neural network architecture search enabled wide-deep learning(NAS-WD)for spatially heterogenous property awared chicken woody breast classification and hardness regression: 《Artificial Intelligence in Agriculture》2024年第4期73-85,共13页Chaitanya Pallerla Yihong Feng Casey M.Owens Ramesh Bahadur Bist Siavash Mahmoudi Pouya Sohrabipour Amirreza Davar Dongyi Wang; support by the University of Arkansas Experimental Station and the University of Arkansas College of Engineering,USDA National Institute of Food and Agriculture (No:2023-70442-39232,2024-67022-42882).; Due to intensive genetic selection for rapid growth rates and high broiler yields in recent years,the global poultry industry has faced a challenging problem in the form of woody breast(WB)conditions.This condition ha...; 关键词：Network architecture search Wide-deep learning BROILER Woody breast Hardness distribution map

Detectability of multi-dimensional movement and behaviour in cattle using sensor data and machine learning algorithms:Study on a updates Charolais bull: 《Artificial Intelligence in Agriculture》2024年第4期86-98,共13页Miklos Biszkup Gabor Vasarhelyi Nuri Nurlaila Setiawan Aliz Marton Szilard Szentes Petra Balogh Barbara Babay-Torok Gabor Pajor Dora Drexler; supported by the Hungarian National Rural Network (Magyar Nemzeti Videki Halozat-MNVH):www.videkihalozat.eu,grant number [VP-20.2.-16-2016-0001].; The development of motion sensors for monitoring cattle behaviour has enabled farmers to predict the state of their cattle's welfare more efficiently.While most studies work with one dimensional output with disjunct b...; 关键词：CATTLE PLF Motion sensors RumiWatch Complex behaviour MULTI-DIMENSIONAL Parallel MACHINELEARNING

Enhancing crop yield prediction in Senegal using advanced machine learning techniques and synthetic data: 《Artificial Intelligence in Agriculture》2024年第4期99-114,共16页Mohammad Amin Razavi A.Pouyan Nejadhashemi Babak Majidi Hoda S.Razavi Josue Kpodo Rasu Eeswaran Ignacio Ciampitti P.V.Vara Prasad; In this study,we employ advanced data-driven techniques to investigate the complex relationships between the yields of five major crops and various geographical and spatiotemporal features in Senegal.We analyze how th...; 关键词：Crop yield prediction Variational auto encoder Pattern recognition on spatiotemporal and physiographical variables Synthetic tabular data generation Ensemble learning

A salient feature establishment tactic for cassava disease recognition: 《Artificial Intelligence in Agriculture》2024年第4期115-132,共18页Jjayu Zhang Baohua Zhang Zixuan Chen Innocent Nyalala Kunjie Chen Junfeng Gao; Accurate classification of cassava disease,particularly in field scenarios,relies on object semantic localization to identify and precisely locate specific objects within an image based on their semantic meaning,there...; 关键词：Cassava disease classification Irrelevant feature depression Semantic foreground representation Salient semantic features Negative eigenvalue maintain

Image classification on smart agriculture platforms:Systematic literature review: 《Artificial Intelligence in Agriculture》2024年第3期1-17,共17页Juan Felipe Restrepo-Arias John W.Branch-Bedoya Gabriel Awad; In recent years,smart agriculture has gained strength due to the application of industry 4.0 technologies in agriculture.As a result,efforts are increasing in proposing artificial vision applications to solvemany prob...; 关键词：Smart agriculture Artificial vision Internet of things Artificial intelligence

《Artificial Intelligence in Agriculture》