Artificial General Segmentation
نویسندگان
چکیده
We argue that the ability to find meaningful chunks in sequential input is a core cognitive ability for artificial general intelligence, and that the Voting Experts algorithm, which searches for an information theoretic signature of chunks, provides a general implementation of this ability. In support of this claim, we demonstrate that VE successfully finds chunks in a wide variety of domains, solving such diverse tasks as word segmentation and morphology in multiple languages, visually recognizing letters in text, finding episodes in sequences of robot actions, and finding boundaries in the instruction of an AI student. We also discuss further desirable attributes of a general chunking algorithm, and show that VE
منابع مشابه
Minimizing Loss of Information at Competitive PLIP Algorithms for Image Segmentation with Noisy Back Ground
In this paper, two training systems for selecting PLIP parameters have been demonstrated. The first compares the MSE of a high precision result to that of a lower precision approximation in order to minimize loss of information. The second uses EMEE scores to maximize visual appeal and further reduce information loss. It was shown that, in the general case of basic addition, subtraction, or mul...
متن کاملTraining Set of Data Bin for Small Black Pixels Neighborhood Recognition of Each Boundary
We first describe how to “fuzzify” the estimated binary columns to create a [0,1]-valued column. Werefer to this [0,1] -valued column as the soft segmentation column of the noisy spectrogram column.Similarly to the collection of soft segmentation columns as the soft segmentation image, or simply asthe soft segmentation. The band-dependent posterior probability that the hard segmentation columnv...
متن کاملA Pixon-based Image Segmentation Method Considering Textural Characteristics of Image
Image segmentation is an essential and critical process in image processing and pattern recognition. In this paper we proposed a textured-based method to segment an input image into regions. In our method an entropy-based textured map of image is extracted, followed by an histogram equalization step to discriminate different regions. Then with the aim of eliminating unnecessary details and achi...
متن کاملSegmentation Assisted Object Distinction for Direct Volume Rendering
Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this work, we are proposing an ...
متن کاملDiagnosis of brain tumor using PNN neural networks
Cells grow and then need a very neat method to create new cells that work properly to maintain the health of the body. When the ability to control the growth of the cells is lost, they are unconsidered and often divided without order. Exemplified cells form a tissue mass called the tumor. In fact, brain tumors are abnormal and uncontrolled cell proliferations. Segmentation methods are used in b...
متن کامل