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DEVELOPMENT OF AN AUTOMATED DEBRIS DETECTION SYSTEM FOR WILD BLUEBERRY HARVESTERS USING A CONVOLUTIONAL NEURAL NETWORK TO IMPROVE FRUIT QUALITY
(2020-11-16)
Improving wild blueberry fruit quality has become increasingly important to producers due to the tightening profit margin facing the industry. The continuous development of field management practices (i.e., application of ...
Stock Movement Prediction with Deep Learning, Finance Tweets Sentiment, Technical Indicators, and Candlestick Charting
(2020-03-31)
Stock prediction has been a popular research topic. Due to its stochastic nature, predicting the future stock market remains a difficult problem. This thesis studies the application of Deep Neural Networks (DNNS) in ...
Convolutional Neural Networks for Real-Time Weed Identification in Wild Blueberry Production
(2020-12-18)
Yield-limiting weeds in wild blueberry fields, including hair fescue and sheep sorrel, are traditionally managed with uniform applications of herbicides. Spot applications of herbicides reduce the volume required for ...
A Machine Learning Framework for Host Based Intrusion Detection using System Call Abstraction
(2020-04-13)
The number of cyber threats is increasing faster than the number of defensive strategies deployed to tackle those threats. An automated Intrusion Detection System (IDS) has the capability to detect, classify, and predict ...
DDOS DETECTION MODELS USING MACHINE AND DEEP LEARNING ALGORITHMS AND DISTRIBUTED SYSTEMS
(2021-01-27)
Distributed Denial-of-Service (DDoS) attacks are considered to be a major security threat to online servers and cloud providers. Intrusion detection systems have utilized machine learning as one of the solutions to the ...
ELECTRONIC GAMING MACHINE PLAYSTYLE DETECTION AND RAPID PLAYSTYLE CLASSIFICATION USING MULTIVARIATE CONVOLUTIONAL LSTM NEURAL NETWORK ARCHITECTURE
(2021-09-01)
Electronic Gaming Machines (EGM) are
common, anonymous, stateless gambling machines operated by a region’s lottery and
situated in licensed venues. Previous work have shown that problem
gambling detection is possible ...
Deep Neural Network (DNN) Design: The Utilization of Approximate Computing and Practical Considerations for Accuracy Evaluation
(2021-08-04)
Approximate computing is emerging as a viable way to achieve significant performance enhancement in terms of power, speed, and area for system on chip (SoC) designs. Utilizing approximate computing in the design of deep ...
Identification of high-frequency periodic acoustic tags with deep learning
(2021-07-30)
Marine life researchers use the concept of fish tracking to determine the activity andbehaviour of fish. It allows the researchers to recognize the valuable biological andphysical support systems required by fish species ...
An Empirical Analysis of Cross-entropy Based and Metric-based Methods on North Atlantic Right Whale Acoustic Data
(2020-06-11)
With increasing concern for marine species extinction, a massive effort has been made to conserve, prevent, and search for a sustainable solution. However, data labeling is a labor-heavy and time-consuming work, resulting ...
COMBINING HIGH-THROUGHPUT IMAGING AND AMPLICON SEQUENCING TO MONITOR EUKARYOTIC PLANKTON
(2021-08-06)
Microbial communities support ocean food webs and respond to the surrounding environment to varying degrees across different time scales. The eukaryotic plankton throughout the oceans are extraordinarily diverse but difficult ...