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Found 10 papers, 1 papers with code
Aligning Multiclass Neural Network Classifier Criterion with Task Performance via $F_β$-Score
Our method extends the $2 \times 2$ binary soft-set confusion matrix to a multiclass $d \times d$ confusion matrix and proposes dynamic adaptation of the threshold value $\tau$, which parameterizes the piecewise-linear Heaviside approximation during run-time.
Predicting Human Impressions of Robot Performance During Navigation Tasks
Further, when predicting robot performance as a binary classification task on unseen users' data, the F1 Score of machine learning models more than doubled in comparison to predicting performance on a 5-point scale.
Principles and Guidelines for Evaluating Social Robot Navigation Algorithms
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation.
Topological Planning with Transformers for Vision-and-Language Navigation
Conventional approaches to vision-and-language navigation (VLN) are trained end-to-end but struggle to perform well in freely traversable environments.
Bridging the Gap: Unifying the Training and Evaluation of Neural Network Binary Classifiers
In this work, we propose a unifying approach to training neural network binary classifiers that combines a differentiable approximation of the Heaviside function with a probabilistic view of the typical confusion matrix values using soft sets.
Improving Social Awareness Through DANTE: A Deep Affinity Network for Clustering Conversational Interactants
We propose a data-driven approach to detect conversational groups by identifying spatial arrangements typical of these focused social encounters.
Deep Local Trajectory Replanning and Control for Robot Navigation
We present a navigation system that combines ideas from hierarchical planning and machine learning.
Conversational Group Detection With Deep Convolutional Networks
Detection of interacting and conversational groups from images has applications in video surveillance and social robotics.
Translating Navigation Instructions in Natural Language to a High-Level Plan for Behavioral Robot Navigation
We propose an end-to-end deep learning model for translating free-form natural language instructions to a high-level plan for behavioral robot navigation.
GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation
We present semi-supervised deep learning approaches for traversability estimation from fisheye images.
