Statistical and machine learning models in credit scoring: A systematic literature survey
X Dastile, T Celik, M Potsane - Applied Soft Computing, 2020 - Elsevier
In practice, as a well-known statistical method, the logistic regression model is used to
evaluate the credit-worthiness of borrowers due to its simplicity and transparency in …
evaluate the credit-worthiness of borrowers due to its simplicity and transparency in …
Recent advances of deep learning algorithms for aquacultural machine vision systems with emphasis on fish
D Li, L Du - Artificial Intelligence Review, 2022 - Springer
Monitoring the growth conditions and behavior of fish will enable scientific management,
reduce the threat of losses caused by disease and stress. Traditional monitoring methods …
reduce the threat of losses caused by disease and stress. Traditional monitoring methods …
RSOD: Real-time small object detection algorithm in UAV-based traffic monitoring
W Sun, L Dai, X Zhang, P Chang, X He - Applied Intelligence, 2022 - Springer
The prevailing applications of Unmanned Aerial Vehicles (UAVs) in transportation systems
promote the development of object detection methods to collect real-time traffic information …
promote the development of object detection methods to collect real-time traffic information …
Detection of solder paste defects with an optimization‐based deep learning model using image processing techniques
A Sezer, A Altan - Soldering & Surface Mount Technology, 2021 - emerald.com
Purpose In the production processes of electronic devices, production activities are
interrupted due to the problems caused by soldering defects during the assembly of surface …
interrupted due to the problems caused by soldering defects during the assembly of surface …
A comprehensive survey of multi-view video summarization
There has been an exponential growth in the amount of visual data on a daily basis
acquired from single or multi-view surveillance camera networks. This massive amount of …
acquired from single or multi-view surveillance camera networks. This massive amount of …
A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges
Distance metric learning is a branch of machine learning that aims to learn distances from
the data, which enhances the performance of similarity-based algorithms. This tutorial …
the data, which enhances the performance of similarity-based algorithms. This tutorial …
Machine learning in marine ecology: an overview of techniques and applications
Abstract Machine learning covers a large set of algorithms that can be trained to identify
patterns in data. Thanks to the increase in the amount of data and computing power …
patterns in data. Thanks to the increase in the amount of data and computing power …
Effective multi-crop disease detection using pruned complete concatenated deep learning model
A significant threat to agriculture yield is crop disease. It leads to enormous losses for
farmers and also has an impact economically. Leaves affected by certain diseases will …
farmers and also has an impact economically. Leaves affected by certain diseases will …
Intelligent and vision-based fire detection systems: A survey
F Bu, MS Gharajeh - Image and vision computing, 2019 - Elsevier
Fire is one of the main disasters in the world. A fire detection system should detect fires in
various environments (eg, buildings, forests, and rural areas) in the shortest time in order to …
various environments (eg, buildings, forests, and rural areas) in the shortest time in order to …
A new deep learning engine for coralnet
CoralNet is a cloud-based website and platform for manual, semi-automatic and automatic
analysis of coral reef images. Users access CoralNet through optimized web-based …
analysis of coral reef images. Users access CoralNet through optimized web-based …