Titlebook: Handwörterbuch der Gerichtlichen Medizin und Naturwissenschaftlichen Kriminalistik; In Gemeinschaft mit F. Neureiter (o. Professor Dr. Med

寄生虫

F. v. Neureiter,F. Pietrusky,E. Schütt4) comprises topics such as visualization; visual computing with multimodal data streams; visual computing in digital cultural heritage; intelligent environments: algorithms and applications; applications; virtual reality.

Breach

Admire

黄油没有

low object resolution. In this work we focus on recognizing objects taken from the xView Satellite Imagery dataset. The xView dataset introduces its own set of challenges, the most prominent being the imbalance between the 60 classes present. xView also contains considerable label noise as well as b

reperfusion

F. v. Neureiter,F. Pietrusky,E. Schüttd subtle inter-class differences. In this paper, we tackle this problem in a weakly supervised manner, where neural network models are getting fed with additional data using a data augmentation technique through a visual attention mechanism. We perform domain adaptive knowledge transfer via fine-tun

不来

辞职

F. v. Neureiter,F. Pietrusky,E. Schüttization within a scene. Recently, convolutional neural networks (CNNs) have been demonstrated to achieve superior detection results compared to traditional approaches. Although YOLOv3 (an improved You Only Look Once model) is proposed as one of state-of-the-art methods in CNN-based object detection,

FECT

F. v. Neureiter,F. Pietrusky,E. Schüttce the benefits of such analysis. This paper presents a novel technique to automatically recover both intrinsic and extrinsic parameters for each surveillance camera within a camera network by only using a walking human. The same feature points of a pedestrian are taken to calculate each camera’s in

CULP

F. v. Neureiter,F. Pietrusky,E. Schütties a series of operators in a pipeline to transform a video stream into shots. These operators are replicated to work in parallel on Flink-managed computing nodes. The V2F deployment of the standard twin-comparison video segmentation method is more than 7 times faster than its non-parallel (i.e., s

biosphere