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Found 10 papers, 3 papers with code
A Multi-Objective Deep Reinforcement Learning Framework
This paper introduces a new scalable multi-objective deep reinforcement learning (MODRL) framework based on deep Q-networks.
Multi-Objective Reinforcement Learning
reinforcement-learning
3D Hand Pose Estimation using Simulation and Partial-Supervision with a Shared Latent Space
In this paper, we propose a novel method that seeks to predict the 3d position of the hand using both synthetic and partially-labeled real data.
A Review of the Family of Artificial Fish Swarm Algorithms: Recent Advances and Applications
Owing to a number of salient properties, which include flexibility, fast convergence, and insensitivity to the initial parameter settings, the family of AFSA has emerged as an effective Swarm Intelligence (SI) methodology that has been widely applied to solve real-world optimization problems.
A Review of Generalized Zero-Shot Learning Methods
Generalized zero-shot learning (GZSL) aims to train a model for classifying data samples under the condition that some output classes are unknown during supervised learning.
An Ensemble Semi-Supervised Adaptive Resonance Theory Model with Explanation Capability for Pattern Classification
Firstly, SSL-ART adopts an unsupervised fuzzy ART network to create a number of prototype nodes using unlabeled samples.
Neural Networks for Fast Optimisation in Model Predictive Control: A Review
Model Predictive Control (MPC) is an optimal control algorithm with strong stability and robustness guarantees.
Machine Learning Meets Advanced Robotic Manipulation
Automated industries lead to high quality production, lower manufacturing cost and better utilization of human resources.
Deep Learning Techniques for Video Instance Segmentation: A Survey
Video instance segmentation, also known as multi-object tracking and segmentation, is an emerging computer vision research area introduced in 2019, aiming at detecting, segmenting, and tracking instances in videos simultaneously.
Current and future roles of artificial intelligence in retinopathy of prematurity
Retinopathy of prematurity (ROP) is a severe condition affecting premature infants, leading to abnormal retinal blood vessel growth, retinal detachment, and potential blindness.
HSViT: Horizontally Scalable Vision Transformer
While the Vision Transformer (ViT) architecture gains prominence in computer vision and attracts significant attention from multimedia communities, its deficiency in prior knowledge (inductive bias) regarding shift, scale, and rotational invariance necessitates pre-training on large-scale datasets.
