LEADER 04658nam 22007455 450 001 9910743346603321 005 20251113191841.0 010 $a981-16-9991-7 010 $a981-16-9990-9 010 $a981-16-9991-7 024 7 $a10.1007/978-981-16-9991-7 035 $a(MiAaPQ)EBC6922465 035 $a(Au-PeEL)EBL6922465 035 $a(CKB)21397525500041 035 $a(PPN)26152240X 035 $a(OCoLC)1303894427 035 $a(DE-He213)978-981-16-9991-7 035 $a(EXLCZ)9921397525500041 100 $a20220313d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputer Vision and Machine Learning in Agriculture, Volume 2 /$fedited by Mohammad Shorif Uddin, Jagdish Chand Bansal 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (269 pages) 225 1 $aAlgorithms for Intelligent Systems,$x2524-7573 311 08$aPrint version: Uddin, Mohammad Shorif Computer Vision and Machine Learning in Agriculture, Volume 2 Singapore : Springer Singapore Pte. Limited,c2022 9789811699900 327 $aHarvesting robots for smart agriculture -- Drone-based weed detection architectures using deep learning algorithms and real-time analytics -- A deep learning-based detection system of multi-class crops and orchards using a UAV -- Real-life agricultural data retrieval for large scale annotation flow optimization -- Design and analysis of IoT-based modern agriculture monitoring system for real time data collection -- Estimation of wheat yield based on precipitation and evapotranspiration using soft computing methods -- Coconut maturity recognition using convolutional neural network -- Agri food products quality assessment methods -- Medicinal plant recognition from leaf images using deep learning -- ESMO based plant leaf disease identification: A machine learning approach -- Deep learning-based cuali flower disease classification -- An Intelligent System for Crop Disease Identification and Dispersion Forecasting in SriLanka -- Apple leaves diseases detection using deep convolutional neural networksand transfer learning -- A deep learning paradigm for detection and segmentation of plant leaves diseases -- Early-stage prediction of plant leaf diseases using deep learning models. 330 $aThis book is as an extension of previous book ?Computer Vision and Machine Learning in Agriculture? for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies. 410 0$aAlgorithms for Intelligent Systems,$x2524-7573 606 $aComputational intelligence 606 $aMachine learning 606 $aRobotics 606 $aAgriculture 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aComputational Intelligence 606 $aMachine Learning 606 $aRobotics 606 $aAgriculture 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 615 0$aComputational intelligence. 615 0$aMachine learning. 615 0$aRobotics. 615 0$aAgriculture. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 14$aComputational Intelligence. 615 24$aMachine Learning. 615 24$aRobotics. 615 24$aAgriculture. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 676 $a338.10285 700 $aUddin$b Mohammad Shorif$01369079 702 $aBansal$b Jagdish Chand 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910743346603321 996 $aComputer vision and machine learning in agriculture$93559244 997 $aUNINA