Our Archive
Spot spraying is a new method. It is based on a concept that only the infected areas of the crop should be sprayed and not the whole field. This novelty can be implemented by having a modern sprayer, electronics and the target to spray in the crop. This last requirement is provided by the image […]
Some posts ago, we were discussing that AutoML is the best way to avoid the overwhelming process of tuning all the hyper-parameters that modify the behavior of a neural network. However, in AutoML you can also choose which hyper-parameters should be the most relevant ones to explore. So the question is: which hyper-parameter should we […]
One high-value crop that needs careful handling both throughout the growing season and during post-harvest care is broccoli. Broccoli heads are still plucked by hand since they are easily damaged. Moreover, to harvest broccoli plants when they are in their best condition, human scouting is also needed to initially locate the field segments where multiple […]
In agriculture, it is really difficult to precisely distinguish the diseases, the pests that have infected your crop, and also some nutrient deficiencies, because of the symptoms’ similarities, especially at the beginning of their emergence. This task, although it seems to be easy even for farmers and agronomists, has the possibility to cause serious problems […]
We know deep learning is one of the main techniques to achieve state-of-the-art performances in computer vision methods applied to agriculture. However, this technique requires very large datasets (thousands of images) so that the automatic feature extraction can work accurately, generalize and not overfit. What can be done if we have a small dataset? There are […]
Yield estimation and mapping in orchards are important for growers as it facilitates efficient utilization of resources and improves returns per unit area and time. With accurate knowledge of yield distribution and quantity, a grower can efficiently manage processes such as use of chemicals, fertilization, and thinning. Yield estimation also allows the grower to plan […]
Which is the best learning rate for your ML pipeline? Do you need a high or a low dropout rate? How many convolutional layers do you need and how many filters? And the most important question: do we really care about these decisions? Most of the time, the answer is no. Although these hyper-parameters can […]
Weeds in the field are the enemy for any crop as they compete with the soil nutrients and can become a host for germs and insects threatening the crops. It is therefore essential to be combated effectively and with as little financial burden as possible for the producer and as little pollution for the environment […]
The first step toward building a computer vision solution is gathering the necessary images and preparing the training dataset. Something of extreme importance for agricultural environments as they are amongst the most challenging due to the constantly changing environmental conditions. Plant’s shape, size, characteristics, and color change throughout the growing season and are heavily dependent […]
“A fertile soil alone does not carry agriculture to perfection” – E. H. DERBY “A Defence of Agriculture”, Lessons in Modern Farming Will you learn to play the piano faster if you previously knew how to play the guitar? Probably, yes. At least some notions on music will boost your learning process with the new instrument. […]