Matches in SemOpenAlex for { <https://semopenalex.org/work/W4226016235> ?p ?o ?g. }
- W4226016235 endingPage "73" @default.
- W4226016235 startingPage "41" @default.
- W4226016235 abstract "Humans have always been intrigued by the notion that a machine could simulate their brain and mimic their actions. For that reason, through the last decades, artificial intelligence became the most prominent field of computer science, aiming to the development of intelligent machines, which are able complete tasks that require high level of cognition. Artificial Intelligence (AI) is a broad area comprised of advanced mathematical methods and computational techniques, such as machine learning and deep learning. Machine learning refers to the mathematical and algorithmic approaches that enable computers to automatically improve their efficiency in particular tasks, without being explicit programming. By analyzing large amount of data, and recognizing the patterns and structures within, machine learning is enables computers to iteratively learn and improve their efficiency without any human interaction. This chapter aims to an introduction towards understanding what machine learning is, by highlighting its differences with conventional programming and pointing out some of its fundamental features. Moreover, different types of machine learning algorithms are described, and examples are given in order to underline their importance in our everyday lives. Finally, a preliminary scholarly literature survey is presented, indicating studies that are referred in machine learning algorithms in the agricultural domain for the years 2018–2020. The study reveals that machine learning can undoubtedly expand our capabilities in many fields of expertise that affect our lives. Specifically in agriculture, machine learning solutions can improve quality of products and significantly increase operational productivity and efficiency." @default.
- W4226016235 created "2022-05-05" @default.
- W4226016235 creator A5042114332 @default.
- W4226016235 creator A5050011641 @default.
- W4226016235 creator A5072450349 @default.
- W4226016235 creator A5079201381 @default.
- W4226016235 date "2022-01-01" @default.
- W4226016235 modified "2023-09-23" @default.
- W4226016235 title "Machine Learning Technology and Its Current Implementation in Agriculture" @default.
- W4226016235 cites W1498436455 @default.
- W4226016235 cites W1498564823 @default.
- W4226016235 cites W1508702903 @default.
- W4226016235 cites W1511814458 @default.
- W4226016235 cites W1541288193 @default.
- W4226016235 cites W1689445748 @default.
- W4226016235 cites W1901616594 @default.
- W4226016235 cites W1973445088 @default.
- W4226016235 cites W1976453866 @default.
- W4226016235 cites W1977556410 @default.
- W4226016235 cites W1985258161 @default.
- W4226016235 cites W1990517717 @default.
- W4226016235 cites W1997453445 @default.
- W4226016235 cites W1999831322 @default.
- W4226016235 cites W2016364915 @default.
- W4226016235 cites W2017113750 @default.
- W4226016235 cites W2022673873 @default.
- W4226016235 cites W2024081693 @default.
- W4226016235 cites W2026498037 @default.
- W4226016235 cites W2036757099 @default.
- W4226016235 cites W2037486322 @default.
- W4226016235 cites W2040870580 @default.
- W4226016235 cites W2056392803 @default.
- W4226016235 cites W2063978378 @default.
- W4226016235 cites W2064675550 @default.
- W4226016235 cites W2083514219 @default.
- W4226016235 cites W2084336274 @default.
- W4226016235 cites W2088897029 @default.
- W4226016235 cites W2089367555 @default.
- W4226016235 cites W2099404336 @default.
- W4226016235 cites W2102201073 @default.
- W4226016235 cites W2105977368 @default.
- W4226016235 cites W2109240653 @default.
- W4226016235 cites W2109993655 @default.
- W4226016235 cites W2119821739 @default.
- W4226016235 cites W2128084896 @default.
- W4226016235 cites W2128728535 @default.
- W4226016235 cites W2146610201 @default.
- W4226016235 cites W2149706766 @default.
- W4226016235 cites W2157331557 @default.
- W4226016235 cites W2158863190 @default.
- W4226016235 cites W2159094788 @default.
- W4226016235 cites W2163922914 @default.
- W4226016235 cites W2164089337 @default.
- W4226016235 cites W2279341026 @default.
- W4226016235 cites W2515895890 @default.
- W4226016235 cites W2555182955 @default.
- W4226016235 cites W2576404523 @default.
- W4226016235 cites W2577820135 @default.
- W4226016235 cites W2582336686 @default.
- W4226016235 cites W2583955450 @default.
- W4226016235 cites W2726539084 @default.
- W4226016235 cites W2738724892 @default.
- W4226016235 cites W2751398324 @default.
- W4226016235 cites W2752782242 @default.
- W4226016235 cites W2766390436 @default.
- W4226016235 cites W2766447205 @default.
- W4226016235 cites W2781967587 @default.
- W4226016235 cites W2782347622 @default.
- W4226016235 cites W2784367312 @default.
- W4226016235 cites W2790858865 @default.
- W4226016235 cites W2790979755 @default.
- W4226016235 cites W2799842361 @default.
- W4226016235 cites W2800002789 @default.
- W4226016235 cites W2801303530 @default.
- W4226016235 cites W2805142011 @default.
- W4226016235 cites W2805267014 @default.
- W4226016235 cites W2805772477 @default.
- W4226016235 cites W2809612736 @default.
- W4226016235 cites W28412257 @default.
- W4226016235 cites W2884367402 @default.
- W4226016235 cites W2885355309 @default.
- W4226016235 cites W2885770726 @default.
- W4226016235 cites W2887972576 @default.
- W4226016235 cites W2895348292 @default.
- W4226016235 cites W2895994027 @default.
- W4226016235 cites W2898498213 @default.
- W4226016235 cites W2901380936 @default.
- W4226016235 cites W2907537824 @default.
- W4226016235 cites W2911666059 @default.
- W4226016235 cites W2911964244 @default.
- W4226016235 cites W2915011392 @default.
- W4226016235 cites W2919115771 @default.
- W4226016235 cites W2921277556 @default.
- W4226016235 cites W2921403460 @default.
- W4226016235 cites W2943419739 @default.
- W4226016235 cites W2944794516 @default.
- W4226016235 cites W2948622240 @default.
- W4226016235 cites W2949079091 @default.