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Deep Reinforcement Learning for Active Human Pose Estimation

Most 3d human pose estimation methods assume that input – be it images of a scene collected from one or several viewpoints, or from a video – is given. Consequently, they focus on estimates leveraging prior knowledge and measurement by fusing information spatially and/or temporally, whenever available. In this paper we address the problem of an active observer with freedom to move and explore the

Single-cell transcriptional and functional analysis of dopaminergic neurons in organoid-like cultures derived from human fetal midbrain

Significant efforts are ongoing to develop refined differentiation protocols to generate midbrain dopamine (DA) neurons from pluripotent stem cells (PSCs) for application in disease modeling, diagnostics, drug screening, and cell-based therapies for Parkinson's Disease (PD). An increased understanding of the timing and molecular mechanisms promoting the generation of distinct subtypes of human mid