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OER Matters

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Keywords: neural

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Animal Behavior, Fall 2001

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Type: Course Related Materials
Subject: Science and Technology
Collection: MIT OpenCourseWare
Grade Level: Post-secondary

Abstract: This course will sample the broad diversity of animal behavior and the behavioral adaptation of animals to the environments in which they live. This will include discussion of both field observations and controlled laboratory experiments. Particular emphasis will be placed on the comparison of behavior ... More »

Foundations of Human Memory and Learning, Spring 2002

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Type: Course Related Materials
Subject: Science and Technology
Collection: MIT OpenCourseWare
Grade Level: Post-secondary

Abstract: Surveys literature on human memory and learning. Focuses on the organization of memory at cognitive and neural levels, the basis of remembering and forgetting, and false memories. Cognitive theory and behavioral evidence are integrated with data from neuro-psychology and neuroimaging.

Introduction to Accent Classification with Neural Networks

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Type: Course Related Materials
Subject: Science and Technology
Collection: Connexions
Grade Level: Post-secondary

Abstract: This module provides an overview of Team SSB's final ELEC 301 project -- accent recognition and classification with a neural network

Neural Network-based Accent Classification Results

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Type: Course Related Materials
Subject: Science and Technology
Collection: Connexions
Grade Level: Post-secondary

Abstract: Listed in this module are output results and analysis of test-audio samples from various speakers, fed to a trained neural network.

Neural Networks

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Type: Course Related Materials
Subject: Science and Technology
Collection: Connexions
Grade Level: Post-secondary

Abstract: Neural networks are a different paradigm for computing based on the parallel architecture of animal brains.

Object and Face Recognition, Spring 2001

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Type: Course Related Materials
Subject: Science and Technology
Collection: MIT OpenCourseWare
Grade Level: Post-secondary

Abstract: Provides a comprehensive introduction to key issues and findings in object recognition in experimental, neural, computational and applied domains. Second half focuses on face recognition. An additional project is required for graduate credit. Alternate years.

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