Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 20 for “"Digit Recognition"”.
-
Discrete HMM isolated digit recognition
… develops an algorithm to perform isolated word recognition. A detailed description of the recognition system is presented in this thesis. We discuss detection of a spoken word from a recording using an end-point algorithm, extraction of the feature vectors from the sampled speech signal, …
-
Continuous HMM connected digit recognition
In this thesis we develop a system for recognition of strings of connected digits that can be used in a hands-free telephone system. We present a detailed description of the elements of the recognition system, such as an endpoint algorithm, the extraction of feature vectors from the speech samples, …
-
Effects of Brain Injury Severity and Effort on Neuropsychological Tests of Attention
… memory were assessed by performance on the Digit Span Forward subtest, the Stroop Color Word Test, the Trail Making Test, the Conners' Continuous Performance Test - II, and Digit Span Backwards subtest, respectively. Effort was determined according to performance on the Portland Digit …
-
Integrating digitizing pen technology and machine learning with the Clock Drawing Test
… learning tools for analysis of CDT results, the digitizing pen has been used to computerize this diagnostic test. In order to successfully integrate digitizing pen technology with the CDT, a digit recognition algorithm was developed to reduce the need for manual classification of the data …
-
Executive Dysfunction following Traumatic Brain Injury and Factors Related to Impairment
… during testing, as measured by the Portland Digit Recognition Test. Results suggested a dose-response relationship between TBI severity and subsequent WCST deficits. Mild TBI patients who provided good effort during testing showed no observable differences from locally matched controls on …
-
Pattern Recognition Using Spiking Neural Networks
… the human brain in specific tasks like pattern recognition in comparison to traditional neural networks convinced neuroscientists to introduce a biologically plausible model of the neuron, which is known as spiking neurons. In opposition to conventional neuron, spiking neurons use a short …
-
Epitaxial SiGe synapses for neuromorphic arrays
… by storing high-precision analog weights between digital processors. However, neuromorphic arrays have not experimentally demonstrated learning accuracy comparable to conventional hardware due to irreproducibility associated with existing artificial synapses. Large variation arises in conventional …
-
Multimodal speech recognition with ultrasonic sensors
… movement is an area of multimodal speech recognition that has not been researched extensively. The widely-researched audio-visual speech recognition (AVSR), which relies upon video data, is awkwardly high-maintenance in its setup and data collection process, as well as computationally …
-
Spiking Neural Network with Memristive Based Computing-In-Memory Circuits and Architecture
… through a small-scale hardware simulation for digit recognition and demonstrate an accuracy of 87% in software through MNIST simulations.
-
Recognition of dates handwritten on cheques
… composed of date image segmentation, handwritten digit recognition, and cursive word recognition. The proposed method does not impose any restriction or require any a priori information on the date written, and is able to handle both English and French cheques. With appropriate modification, this …
-
Validation of the Memory Attention Concentration Evaluation
… the evaluation for malingering. The Portland Digit Recognition Test (PORT; Binder & Willis, 1991) has been found to be a valid measure of a client's motivation to perform inadequately on memory evaluations and thus, detects clients attempting to memory malinger. The PORT takes approximately 45 …
-
Techniques in support vector classification
… materials design problem and to a handwritten digit recognition problem. Finally, we consider the problem of training Support Vector Machines. Specifically, we develop a fast method for obtaining the coefficients αi and βj in (*). Traditionally, these coefficients are found by solving a …
-
Adaptive function modal learning neural networks
… the Iris dataset, and a natural language phrase recognition task. A multi-layer approach, a Multi-layer ADFUNN (MADFUNN) is introduced to solve highly complex datasets. It aims to find a suitably restricted subset of neuron activation functions which has a good representational capacity and …
-
Energy-efficient smart embedded memory design for IoT and AI
… better energy-efficiency than conventional digital implementations. With our variation-tolerant architecture and support of multi-bit resolutions for inputs/outputs, > 98% classication accuracy was demonstrated on the MNIST dataset, for the handwritten digit recognition application. In the …
-
Detecting worm mutations using machine learning
… have been shown to be well suited to pattern recognition tasks such as text categorisation and hand-written digit recognition. Since detecting worms is effectively a pattern recognition problem, this work investigates how well Support Vector Machines perform at this task. The second part of …
-
Sparse modeling of high-dimensional data for learning and vision
… image classification, and experiments on object recognition, scene classification, face recognition, gender recognition, and handwritten digit recognition all lead to state-of-the-art performances on the benchmark datasets. We cast the image super-resolution problem as one of recovering a …
-
Active evaluation of predictive models
… such as spam filtering, face and handwritten digit recognition, and personalized product recommendation. In general, they are used to predict a target label for a given data instance. In order to make an informed decision about the deployment of a predictive model, it is crucial to know the …
-
Implementation of a Connected Digit Recognizer Using Continuous Hidden Markov Modeling
… implementation of a speaker dependent connected-digit recognizer using continuous Hidden Markov Modeling (HMM). The speech recognition system was implemented using MATLAB and on the ADSP-2181, a digital signal processor manufactured by Analog Devices. Linear predictive coding (LPC) analysis was …
-
Adaptive Effort Classifiers: A System Design For Partitioned Edge/Cloud Inference
… datasets viz.MNIST dataset for handwritten digit recognition and CIFAR-10 dataset for object recognition. We demonstrate up to 3.44×-11.29×improvement in ops with no loss in accuracy.</p>
-
Deep in-memory computing
… as compared to the conventional 8-b fixed-point digital implementation optimally designed for each algorithm. Then, DIMA also has been applied to more complex algorithms: (1) convolutional neural network (CNN), (2) sparse distributed memory (SDM), and (3) random forest (RF). System-level …