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Farms

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Individual identification of dairy cows based on deep learning and feature fusion.

Animal science journal = Nihon chikusan Gakkaiho
Individual identification of dairy cows is one of the most important prerequisites for an intelligent dairy farming. Herein, a new method of individual identification of dairy cows based on the fusion of deep and shallow features of dairy cow's trunk...

A Crop Growth Prediction Model Using Energy Data Based on Machine Learning in Smart Farms.

Computational intelligence and neuroscience
In the recent past, the agricultural industry has rapidly digitalized in the form of smart farms through the broad usage of data analysis and artificial intelligence. Commonly, high operating costs in a smart farm are primarily due to inefficient ene...

Network Architecture for Intelligent Identification of Faults in Rabbit Farm Environment Monitoring Based on a Biological Neural Network Model.

Computational intelligence and neuroscience
Currently, livestock and poultry farming is gradually developing towards modernization and scale, and closed livestock and poultry farms are widely used for poultry feeding management, but at the same time, the farming risks of large-scale farms are ...

DEVELOPMENT OF A ROBOT FOR THE MEASUREMENT OF RADIOACTIVE CONTAMINATION AND FERTILITY OF THE SOIL IN FARMLAND.

Radiation protection dosimetry
A tractor-based robot with the capability of real-time assessing and visualizing the radioactive material density and fertility distribution of farmlands has been developed to accelerate the recovery process of the farmlands suffered by the accident ...

Livestock Identification Using Deep Learning for Traceability.

Sensors (Basel, Switzerland)
Farm livestock identification and welfare assessment using non-invasive digital technology have gained interest in agriculture in the last decade, especially for accurate traceability. This study aimed to develop a face recognition system for dairy f...

Sensor-Driven Human-Robot Synergy: A Systems Engineering Approach.

Sensors (Basel, Switzerland)
Knowledge-based synergistic automation is a potential intermediate option between the opposite extremes of manual and fully automated robotic labor in agriculture. Disruptive information and communication technologies (ICT) and sophisticated solution...

Farmland quality assessment using deep fully convolutional neural networks.

Environmental monitoring and assessment
Farmland is the cornerstone of agriculture and is important for food security and social production. Farmland assessment is essential but traditional methods are usually expensive and slow. Deep learning methods have been developed and widely applied...

Research on the evaluation method of agricultural intelligent robot design solutions.

PloS one
BACKGROUND: At present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growt...

Comparing State-of-the-Art Deep Learning Algorithms for the Automated Detection and Tracking of Black Cattle.

Sensors (Basel, Switzerland)
Effective livestock management is critical for cattle farms in today's competitive era of smart modern farming. To ensure farm management solutions are efficient, affordable, and scalable, the manual identification and detection of cattle are not fea...

Early Identification of Crop Type for Smallholder Farming Systems Using Deep Learning on Time-Series Sentinel-2 Imagery.

Sensors (Basel, Switzerland)
Climate change and the COVID-19 pandemic have disrupted the food supply chain across the globe and adversely affected food security. Early estimation of staple crops can assist relevant government agencies to take timely actions for ensuring food sec...