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Found 9 papers, 4 papers with code
Challenges in Visual Anomaly Detection for Mobile Robots
We consider the task of detecting anomalies for autonomous mobile robots based on vision.
Training Lightweight CNNs for Human-Nanodrone Proximity Interaction from Small Datasets using Background Randomization
We consider the task of visually estimating the pose of a human from images acquired by a nearby nano-drone; in this context, we propose a data augmentation approach based on synthetic background substitution to learn a lightweight CNN model from a small real-world training set.
Sensing Anomalies as Potential Hazards: Datasets and Benchmarks
We consider the problem of detecting, in the visual sensing data stream of an autonomous mobile robot, semantic patterns that are unusual (i. e., anomalous) with respect to the robot's previous experience in similar environments.
Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches
We consider the task of controlling a quadrotor to hover in front of a freely moving user, using input data from an onboard camera.
Learning Long-range Perception using Self-Supervision from Short-Range Sensors and Odometry
We introduce a general self-supervised approach to predict the future outputs of a short-range sensor (such as a proximity sensor) given the current outputs of a long-range sensor (such as a camera); we assume that the former is directly related to some piece of information to be perceived (such as the presence of an obstacle in a given position), whereas the latter is information-rich but hard to interpret directly.
Robotics
Assessment of algorithms for mitosis detection in breast cancer histopathology images
The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers.
Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks
Deep Neural Networks now excel at image classification, detection and segmentation.
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
The input layer maps each window pixel to a neuron.
High-Performance Neural Networks for Visual Object Classification
We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants.
