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Agriculture is being made more efficient and more profitable by a new generation of computer vision based AI applications. These machine learning driven models can analyse crops and livestock and accurately infer a range of information from what they see. The implications of this technology are significant, precision agriculture will

The COVID-19 pandemic has further accelerated the ongoing shift towards internet shopping and home delivery. Delivery giant Amazon reported a near 200% rise in profits in 2020, cementing at home shopping as the dominant consumer habit for the coming decades. As demand for delivery services accelerate computer vision based AI

What is video annotation Many computer vision models are designed to interpret and operate within chaotic, moving, real-world environments. Video annotation helps AI to function effectively in these spaces by applying information to video footage. This information is generally added to videos by human annotators who apply outlines and labels

Defining image annotation Image annotation gives machine learning models information about what a given image is showing. In most cases this information is applied to datasets by human annotators who highlight and label relevant parts of images in accordance with the needs of machine learning developers. Image annotation allows researchers

Three types of image annotation can be used to train your computer vision model: image classification, object detection, and segmentation. Image classification and object detection are fairly straightforward — the former involves labeling the object featured in an image while the latter takes the same process a step further by introducing

Smart livestock farming has the potential to meet the challenges of food production in the twenty-first century. Computer vision based AI monitoring systems have the capacity to support farmers and improve animal welfare, whilst promoting efficiency and productivity. Livestock management is being transformed by machine learning models that can manage

Reliable emotion detection is one of the holy grails of deep learning and AI research. The creation of AI models that are consistently able to recognise and contextualise human emotions promises revolutionary applications across a number of industries. Widespread deployment of this technology will allow companies and other organisations to