Kim Arild Steen

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In agricultural mowing operations, thousands of animals are injured or killed each year, due to the increased working widths and speeds of agricultural machinery. Detection and recognition of wildlife within the agricultural fields is important to reduce wildlife mortality and, thereby, promote wildlife-friendly farming. The work presented in this paper(More)
During the last decades, high-efficiency farming equipment has been developed in the agricultural sector. This has also included efficiency improvement of moving techniques, which include increased working speeds and widths. Therefore, the risk of wild animals being accidentally injured or killed during routine farming operations has increased dramatically(More)
Ever since smartphones reached the general public, developers have been exploring the vast opportunities they provide. With their increasing number of sensors and processing power, we have now reached a point where the phones can collect and process large amounts of data. In this paper we present an Android application developed for acoustic pattern(More)
Since human-wildlife conflicts are increasing, the development of cost-effective methods for reducing damage or conflict levels is important in wildlife management. A wide range of devices to detect and deter animals causing conflict are used for this purpose, although their effectiveness is often highly variable, due to habituation to disruptive or(More)
In this paper, an algorithm for obstacle detection in agricultural fields is presented. The algorithm is based on an existing deep convolutional neural net, which is fine-tuned for detection of a specific obstacle. In ISO/DIS 18497, which is an emerging standard for safety of highly automated machinery in agriculture, a barrel-shaped obstacle is defined as(More)
The concept of autonomous farming concerns automatic agricultural machines operating safely and efficiently without human intervention. In order to ensure safe autonomous operation, real-time risk detection and avoidance must be undertaken. This paper presents a flexible vehicle-mounted sensor system for recording positional and imaging data with a total of(More)
Mechanical weeding is an important tool in organic farming. However, the use of mechanical weeding in conventional agriculture is increasing, due to public demands to lower the use of pesticides and an increased number of pesticide-resistant weeds. Ground nesting birds are highly susceptible to farming operations, like mechanical weeding, which may destroy(More)
Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily(More)
Current frightening devices are inefficient, because of habituation. This paper presents concepts and algorithms for an adaptive frightening device, which is capable of measuring its own success and thereby alter frightening strategies if beginning habituation is observed. The framework includes acoustic detection and recognition of conflict species and(More)