Crop emergence counting in cereals is labor-intensive and becomes tricky when plants start to overlap. We at Pheno-Inspect GmbH offer you a solution based on RGB images that allows you to count and evaluate your trials’ performance. For example, you can fly with an out-of-the-box Phantom 4 Pro, send us the raw image data, and…

Our AI-based “counting experts” can detect #anycrop, whether it is a row crop or not, and reliably count individual plants under most conditions in the field, thus detecting gaps and generating dynamic traits over time. It does not matter:(i) if plants have just emerged,(ii) if plants already overlap each other,(iii) if there is high weed pressure…

Our AI-based “digital experts” can detect and map different plant species in the field. We unleash the full potential of high-resolution aerial photography to detect and map crops and various weeds.

One of our AI-based “digital experts” is practiced in detecting, counting, and analyzing ears. Either from aerial images taken by a commercial RGB-only drone, a smartphone, or any other camera. Would you also like to count ears or #anyotherobjects in your trial fields fully automatically and with high throughput?Do not hesitate to contact us, and we can…

Trait assessments in field trials are nowadays carried out with high personnel demand. We at Pheno-Inspect GmbH develop state-of-the-art, cloud-based image processing software based on artificial intelligence for the agricultural and plant breeding sector and make it available worldwide. Automated counting, sizing several crops and weeds, detecting plant stress, and many other traits are just a few…

We are proud to announce that our paper is nominated for the Best Paper Award on Agri-Robotics on the International Conference on Intelligent Robots and Systems (IROS 2020). “Unsupervised Domain Adaptation for Transferring Plant Classification Systems to New Field Environments, Crops, and Robots.” Paper: Link Great work together with Dario Gogoll, Jan Weyler, Cyrill Stachniss and Nik Petrinic.

We, Pheno-Inspect GmbH, together with the manufacturer of autonomous drones for greenhouses Corvus Drones and the horticultural and knowledge development partner Botany, have submitted a #Eurostars project application. The focus is on the automation of cultivation processes and procedures for tomato cultivation within greenhouses.

Trait assessments in the field, i.e., the visual evaluation of the plants’ phenotype, are nowadays carried out with high personnel demand and cost. In part, relevant plant characteristics cannot yet be recorded (non-destructively) with today’s technology. We develop state-of-the-art, cloud-based image processing software based on artificial intelligence for the agricultural and plant breeding sector. Here…

We are happy to announce that Pheno-Inspect joined the Space2Agriculture network today. The network consists of small and medium-sized enterprises, large companies, start-ups, universities, and research institutions and opens up a communication platform between space and agriculture. The network aims to establish cross-sectoral networking, to initiate and consolidate synergies. New commercialization potentials are to be…

Another AI-based “digital expert” from our portfolio is specialized in the analysis of maize plants and the generation of field status reports. It identifies both individual plants and weeds using RGB image data obtained from commercial drones. Our digital expert robustly detects individual plants at different growth stages, even in scenarios with substantial overlap. We…