Results 61 to 70 of about 9,750,100 (244)

Study to Determine Levels of Cadmium in Cocoa Crops Applied to Inland Areas of Peru: “The Case of the Campo Verde-Honoria Tournavista Corridor”

Agronomy, 2020
The presence of cadmium (Cd) in cocoa crops is currently a serious problem for farmers and producers in various regions of South America. Because its exports of cocoa and derivatives to European markets are threatened by possible signs of contamination ...
Jimmy Aurelio Rosales-Huamani, Jorge Luis Breña-Ore, Svitlana Sespedes-Varkarsel, Luis Huamanchumo de la Cuba, Luis Centeno-Rojas, Alonso Otiniano-Zavala, Joseps Andrade-Choque, Santiago Valverde-Espinoza, Jose Luis Castillo-Sequera   +8 more
doaj   +1 more source

A Novel Application of Ensemble Methods with Data Resampling Techniques for Drill Bit Selection in the Oil and Gas Industry

Energies, 2021
Selection of the most suitable drill bit type is an important task for drillers when planning for new oil and gas wells. With the advancement of intelligent predictive models, the automated selection of drill bit type is possible using earlier drilled ...
Saurabh Tewari, Umakant Dhar Dwivedi, Susham Biswas   +2 more
doaj   +1 more source

Self-supervision advances morphological profiling by unlocking powerful image representations

Scientific Reports
Cell Painting is an image-based assay that offers valuable insights into drug mechanisms of action and off-target effects. However, traditional feature extraction tools such as CellProfiler are computationally intensive and require frequent parameter ...
Vladislav Kim, Nikolaos Adaloglou, Marc Osterland, Flavio M. Morelli, Marah Halawa, Tim König, David Gnutt, Paula A. Marin Zapata   +7 more
doaj   +1 more source

Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN Algorithms on Eleven Different Datasets from UCI Machine Learning Repository

, 2018
Machine learning qualifies computers to assimilate with data, without being solely programmed [1, 2]. Machine learning can be classified as supervised and unsupervised learning.
Arif, Rezoana Bente, Khan, Mohammad Mahmudur Rahman, Oishe, Mahjabin Rahman, Siddique, Md. Abu Bakr   +3 more
core   +1 more source

Econometrics and Machine Learning [PDF]

Economie et Statistique / Economics and Statistics, 2019
On the face of it, econometrics and machine learning share a common goal : to build a predictive model, for a variable of interest, using explanatory variables (or features). However, the two fields have developed in parallel, thus creating two different cultures.
Charpentier, Arthur, Flachaire, Emmanuel, Ly, Antoine   +2 more
openaire   +4 more sources

Monitoring the lactation-related behaviors of sows and their piglets in farrowing crates using deep learning

Frontiers in Animal Science
Pig farming is a major sector of livestock production. The preweaning stage is a critical period in the pig farming process, where lactation-related behaviors between sows and their piglets directly influence the preweaning survivability of the piglets ...
Yu-Jung Tsai, Yi-Che Huang, En-Chung Lin, Sheng-Chieh Lai, Xu-Chu Hong, Jonas Tsai, Cheng-En Chiang, Yan-Fu Kuo   +7 more
doaj   +1 more source

MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning

Entropy, 2019
Efficient approximation lies at the heart of large-scale machine learning problems. In this paper, we propose a novel, robust maximum entropy algorithm, which is capable of dealing with hundreds of moments and allows for computationally efficient ...
Diego Granziol, Binxin Ru, Stefan Zohren, Xiaowen Dong, Michael Osborne, Stephen Roberts   +5 more
doaj   +1 more source

Objective criteria for explanations of machine learning models

Applied AI Letters, 2021
Objective criteria to evaluate the performance of machine learning (ML) model explanations are a critical ingredient in bringing greater rigor to the field of explainable artificial intelligence.
Chih‐Kuan Yeh, Pradeep Ravikumar
doaj   +1 more source

Automatic generation of hardware Tree Classifiers [PDF]

, 2017
Machine Learning is growing in popularity and spreading across different fields for various applications. Due to this trend, machine learning algorithms use different hardware platforms and are being experimented to obtain high test accuracy and ...
Thanjavur Bhaaskar, Kiran Vishal
core  

Qudit machine learning

Machine Learning: Science and Technology
Abstract We present a comprehensive investigation into the learning capabilities of a simple d-level system (qudit). Our study is specialized for classification tasks using real-world databases, specifically the Iris, breast cancer, and MNIST datasets.
Sebastián Roca-Jerat, Juan Román-Roche, David Zueco   +2 more
openaire   +6 more sources