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Video Object Detection Based on Deformable Convolution
Video object detection is one of the important research directions in the field of computer vision with applications in various domains, e.g. public security, traffic management, etc. Nevertheless, it is very challenging to extend the image-based object ...
Ship Detection in Satellite Optical Imagery
Deep learning ship detection in satellite optical imagery suffers from false positive occurrences with clouds, landmasses, and man-made objects that interfere with correct classification of ships, typically limiting class accuracy scores to 88%. This ...
Video Tampering Detection based on High-Frequency Features using Machine Learning
In recent times, security cameras can be found installed in various places such as lobbies of buildings, urban areas, and drive recorders in automobiles. Similarly, smartphones and drive recorders have become a part of our everyday lives. However, in ...
Detecting Discrete Cosine Transform-Based Digital Watermarking Insertion Area Using Deep Learning
Invisible digital watermarking, a technology for embedding information in digital content, is mainly used for copyright protection. In this paper, we proposed a method to identify images with invisible discrete cosine transform (DCT)-based watermarking ...
CNN as a feature extractor in gaze recognition
In this paper, we employ a Convolutional Neural Network (CNN) in predicting physician gaze. This paper focuses on two aspects – one comparison between hand-crafted features and CNN-based learned features, and two in investigating the impact of fully-...
Prediction of lung and colon cancer through analysis of histopathological images by utilizing Pre-trained CNN models with visualization of class activation and saliency maps
Colon and Lung cancer is one of the most perilous and dangerous ailments that individuals are enduring worldwide and has become a general medical problem. To lessen the risk of death, a legitimate and early finding is particularly required. In any case,...
Resolving Lexical Ambiguity in English-Japanese Neural Machine Translation
Although Lexical ambiguity, i.e., the presence of two or more meanings for a single word, is an inherent and challenging problem for machine translation systems. Even though the use of recurrent neural networks (RNN) and attention mechanisms are ...
The Walking Robot Based on Mechanical Connecting-rod
In recent years, China's investment in space technology and natural environment has been increasing. In recent years, China's investment in space technology and natural environment has been increasing. First of all, it must be the bionic robot with ...
Development of Robotic Quiz Games for Self-Regulated Learning of Primary School Children
The progressive development of information technology has provided multiple learning modes. The rich content and innovative applications available allow pupils to improve their skills through self-regulated learning (SRL), which has become an important ...
How Do We Predict Stock Returns in the Cross-Section with Machine Learning?
Stock return prediction is one of the most important themes for investors. Until now, there are many studies for the application of machine learning methods to predict stock returns in the cross-section. However, those studies focus only on differences ...
Indoor Location Estimation Based on Inverse Fingerprints at Multiple Points in Time and Moving Distance
In indoor position estimation, it is generally difficult to estimate the coordinates accurately using indoor localization methods such as fingerprinting, triangulation and pedestrian dead reckoning alone. This is because each method has its own ...
Towards Diagnosis of Carpal Tunnel Syndrome Using Machine Learning
Carpal Tunnel Syndrome (CTS) is the most common peripheral neuropathy affecting the hand function. Although the most complains from patients with CTS are fine motor control failures in daily manual activities, parameters of hand functional control have ...
A Systematic Review on Anomaly Detection for Cloud Computing Environments
The detection of anomalies in data is a far-reaching field of research which also applies to the field of cloud computing in several different ways: from the detection of various types of intrusions to the detection of hardware failures, many ...
Live Monitoring of Speech Quality of Public Addressing Network Speakers: A Preliminary Study
There are a growing number of installations of network speakers in public space like train stations, schools, and hospitals. These speakers are used for announcements and playing background music. Network performance can affect the quality of ...
Effective Tuning of Regression Models using an Evolutionary Approach: A Case Study
Hyperparameters enable machine learning algorithms to be customized for specific datasets. Choosing the right hyperparameters is a challenge often faced by machine learning practitioners. With this research, tuning of hyperparameters for regression ...
Using Twitter Social Media for Depression Detection in the Canadian Population
Depression is a serious public health problem, and an economic burden for the society. Therefore, identifying individuals with depression and providing the support for the people in need is a crucial step for creating a healthier environment. In this ...
Index Terms
- Proceedings of the 2020 3rd Artificial Intelligence and Cloud Computing Conference