Integrating scientific knowledge with machine learning for engineering and environmental systems
There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …
require novel methodologies that are able to integrate traditional physics-based modeling …
The elements of end-to-end deep face recognition: A survey of recent advances
Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …
vision. With the recent development of deep learning techniques and large-scale datasets …
Omnivore: A single model for many visual modalities
Prior work has studied different visual modalities in isolation and developed separate
architectures for recognition of images, videos, and 3D data. Instead, in this paper, we …
architectures for recognition of images, videos, and 3D data. Instead, in this paper, we …
Ultra fast deep lane detection with hybrid anchor driven ordinal classification
Modern methods mainly regard lane detection as a problem of pixel-wise segmentation,
which is struggling to address the problems of efficiency and challenging scenarios like …
which is struggling to address the problems of efficiency and challenging scenarios like …
Learning auxiliary monocular contexts helps monocular 3d object detection
Monocular 3D object detection aims to localize 3D bounding boxes in an input single 2D
image. It is a highly challenging problem and remains open, especially when no extra …
image. It is a highly challenging problem and remains open, especially when no extra …
Multi-task learning as a bargaining game
In Multi-task learning (MTL), a joint model is trained to simultaneously make predictions for
several tasks. Joint training reduces computation costs and improves data efficiency; …
several tasks. Joint training reduces computation costs and improves data efficiency; …
[图书][B] Lifelong machine learning
Z Chen, B Liu - 2022 - books.google.com
Lifelong Machine Learning, Second Edition is an introduction to an advanced machine
learning paradigm that continuously learns by accumulating past knowledge that it then …
learning paradigm that continuously learns by accumulating past knowledge that it then …
Sparse local patch transformer for robust face alignment and landmarks inherent relation learning
Heatmap regression methods have dominated face alignment area in recent years while
they ignore the inherent relation between different landmarks. In this paper, we propose a …
they ignore the inherent relation between different landmarks. In this paper, we propose a …
Multitask hypergraph convolutional networks: A heterogeneous traffic prediction framework
J Wang, Y Zhang, L Wang, Y Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Traffic prediction methods on a single-source data have achieved excellent results in recent
years, especially the Graph Convolutional Networks (GCN) based models with spatio …
years, especially the Graph Convolutional Networks (GCN) based models with spatio …
Deep learning-based multi-task prediction system for plant disease and species detection
The manual prediction of plant species and plant diseases is expensive, time-consuming,
and requires expertise that is not always available. Automated approaches, including …
and requires expertise that is not always available. Automated approaches, including …