Abstract: This disclosure relates to improved systems, methods, and techniques for constructing and employing neural network architectures to solve computer vision and other problems. The neural network architectures can have two or three layers with all nodes in the first layer connected to all nodes in the second layer. The nodes in the second layer can be connected to each other. The weights or values of the various connections between these nodes in the first two layers can also be updated between the processing of inputs to the neural network architectures. These neural network architectures do not require extensive training and can learn continuously. Other embodiments are disclosed herein as well.

Abstract: This disclosure relates to improved systems, methods, and techniques for constructing and employing neural network architectures to solve computer vision and other problems. The neural network architectures can have two or three layers with all nodes in the first layer connected to all nodes in the second layer. The nodes in the second layer can be connected to each other. The weights or values of the various connections between these nodes in the first two layers can also be updated between the processing of inputs to the neural network architectures. These neural network architectures do not require extensive training and can learn continuously. Other embodiments are disclosed herein as well.

Abstract: The present invention provides compositions, combinations, methods, sequences and kits for use of novel fluorescent proteins derived from the genus Branchiostoma. Specifically, polynucleotide and polypeptide sequences encoding fluorescent proteins isolated from Branchiostoma floridae, including harmonized sequences, which permit enhanced expression of the encoded polypeptides in mammalian cells in vivo are provided.