HAND POSE ESTIMATION

A neural network in multi-task deep learning paradigm for machine vision includes an encoder that further includes first, second, and third tiers. The second tier receives a first tier output from the first tier at one or more second tier units in the second tier. The third tier receives a second tier output from the second tier at one or more third tier units in the third tier. The first, second, and third tier units each comprise one or more first, second, and third tier blocks respectively. The neural network further comprises a decoder operatively coupled to the encoder to receive an encoder output from the encoder as well as one or more loss function layers that are configured to backpropagate one or more losses for training at least the encoder of the neural network in a deep learning paradigm. 用于机器视觉的采用多任务深度学习范式的神经网络包括进一步包括第一层、第二层和第三层的编码器。第二层在第二层中的一个或多个第二层单元处从第一层接收第一层输出。第三层在第三层中的一个或多个第三层单元处从第二层接收第二层输出。第一、第二和第三层单元每个分别包括一个或多个第一、第二和第三层区块。神经网络进一步包括：解码器，其可操作地耦合到编码器以接收来自编码器的编码器输出；以及一个或多个损失函数层，其被配置为反向传播一个或多个损