TY  - GEN
N2  - This book is as an extension of the previous two volumes on Computer Vision and Machine Learning in Agriculture. This volume 3 discusses solutions to the problems of agricultural production by rendering advanced machine learning including deep learning tools and techniques. The book contains 13 chapters that focus on in-depth research outputs in precision agriculture, crop farming, horticulture, floriculture, vertical farming, animal husbandry, disease detection, plant recognition, production yield, product quality, defect assessment, and overall automation through robots and drones. The topics covered in the current volume, along with the previous volumes, are comprehensive literature for both beginners and experienced in this domain.
DO  - 10.1007/978-981-99-3754-7
DO  - doi
AB  - This book is as an extension of the previous two volumes on Computer Vision and Machine Learning in Agriculture. This volume 3 discusses solutions to the problems of agricultural production by rendering advanced machine learning including deep learning tools and techniques. The book contains 13 chapters that focus on in-depth research outputs in precision agriculture, crop farming, horticulture, floriculture, vertical farming, animal husbandry, disease detection, plant recognition, production yield, product quality, defect assessment, and overall automation through robots and drones. The topics covered in the current volume, along with the previous volumes, are comprehensive literature for both beginners and experienced in this domain.
T1  - Computer vision and machine learning in agriculture.
DA  - 2023.
CY  - Singapore :
AU  - Bansal, Jagdish Chand.
AU  - Uddin, Mohammad Shorif.
CN  - S494.5.D3
PB  - Springer,
PP  - Singapore :
PY  - 2023.
N1  - 4 Model Architecture
ID  - 1472290
KW  - Artificial intelligence
KW  - Computer vision.
KW  - Machine learning.
SN  - 9789819937547
SN  - 981993754X
TI  - Computer vision and machine learning in agriculture.
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-3754-7
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-3754-7
ER  -