Academic Articles & Research Papers

Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning—A Comparison between High-End and Low-Cost Multispectral Sensors

In order to meet the increasing demand for crops under challenging climate conditions, efficient and sustainable cultivation strategies are becoming essential in agriculture. Targeted herbicide use reduces environmental pollution and effect...

The Effects of Gender Signals and Performance in Online Product Reviews

This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are...

Editorial: Deep learning for high-dimensional sense, non-linear signal processing and intelligent diagnosis

Deep Learning in Chemistry

Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns repres...

Deep Learning: Methods and Applications

This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise...

Deep learning in agriculture: A survey

Deep Learning

An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vi...

Deep Learning

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...

Machine Learning

Availability-Aware Multitask Learning for Robust Clinical Prediction from Incomplete Electronic Health Records

This study presents NORIA, an availability-aware multitask learning framework for clinical prediction from incomplete electronic health records (EHRs). We analyzed a public dataset of 77,724 patients and 107 numerical features. To prevent t...

Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and th...

Machine Learning Refined

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuiti...

Machine Learning and Cybernetics

Advanced Lectures on Machine Learning

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19

Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...

DaDianNao: A Machine-Learning Supercomputer

Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...

Some Studies in Machine Learning Using the Game of Checkers

Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it will learn to play a better game of checkers than ca...

New Advances in Machine Learning

The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call “learning” tasks...

Machine Learning for Hackers

If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John...

Proactive caching in cloud and D2D assisted multi-tier cellular networks

Proactive caching in multi-tier cellular networks (MTCNs) is an efficient technique for alleviating heavy data traffic on backhaul links, thereby reducing content latency and increasing the overall cache hit ratio (CHR) and user satisfactio...