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Found 6 papers, 3 papers with code
AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets
Since the modern deep neural networks are of sophisticated design with complex architecture for the accuracy reason, the diversity on distributions of weights and activations is very high.
Error Loss Networks
A novel model called error loss network (ELN) is proposed to build an error loss function for supervised learning.
CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection
CentripetalNet predicts the position and the centripetal shift of the corner points and matches corners whose shifted results are aligned.
Visual Semantic SLAM with Landmarks for Large-Scale Outdoor Environment
Semantic SLAM is an important field in autonomous driving and intelligent agents, which can enable robots to achieve high-level navigation tasks, obtain simple cognition or reasoning ability and achieve language-based human-robot-interaction.
Asymmetric Correntropy for Robust Adaptive Filtering
Correntropy is generally defined as the expectation of a Gaussian kernel between two random variables.
Multi-Kernel Correntropy for Robust Learning
In a recent work, the concept of mixture correntropy (MC) was proposed to improve the learning performance, where the kernel function is a mixture Gaussian kernel, namely a linear combination of several zero-mean Gaussian kernels with different widths.
