Smart Sensing Technologies for Agriculture

• Autore: Adamchuk Viacheslav
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 electronic resource (232 p.)
• Soggetto topico: History of engineering & technology
• Soggetto non controllato: moisture measurement; Kalman filter; model predictive control; germination paper; convolutional neural networks; livestock; lying posture; standing posture; Three-dimensional mapping; quasi-3D inversion algorithm; cation exchange capacity; clay content; sandy infertile soil; optical micro-sensors; crop protection; precision agriculture; infrared spectroscopy; principal component analysis (PCA); partial least squares (PLS); droplet characterization; apparent electrical conductivity (ECa); pH; UAV; boundary-line; quantile regression; law of minimum; on-site detection; ion-selective electrode (ISE); soil nitrate nitrogen (NO3−-N); soil moisture; sensor fusion; transfer learning; deep learning; body dimensions; point cloud; Kd-network; feature recognition; FFPH; non-contact measurement; X-ray fluorescence; spectroscopy; soil nutrients; proximal soil sensing; soil testing; laser-induced breakdown spectroscopy; LIBS; elemental composition; broiler surface temperature extraction; thermal image processing; head region locating; adaptive K-means; ellipse fitting; harvesting robot; gripper; segmentation; cutting point detection; soil; soil electrical resistivity; autonomous robot; real-time measurement; precision farming; mapping; precision weeding; multispectral imaging; kinetic stereo imaging; plant detection; yield estimation; machine vision; willow tree
• Persona (resp. second.): SudduthKenneth; BiswasAsim; AdamchukViacheslav
• Sommario/riassunto: “Smart Sensing Technologies for Agriculture” is a Special Issue of Sensors that includes 14 research papers on diverse topics about the measurement of physical, chemical, and biological characteristics of soil, plants, and animals related to modern farming practices.
• Titolo autorizzato: Smart Sensing Technologies for Agriculture
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557667303321
• Lo trovi qui: Univ. Federico II