A review of convolutional neural network applied to fruit image processing
J Naranjo-Torres, M Mora, R Hernández-García… - Applied Sciences, 2020 - mdpi.com
Agriculture has always been an important economic and social sector for humans. Fruit
production is especially essential, with a great demand from all households. Therefore, the …
production is especially essential, with a great demand from all households. Therefore, the …
Classification of sour lemons based on apparent defects using stochastic pooling mechanism in deep convolutional neural networks
Quality assessment of agricultural products is one of the most important factors in promoting
their marketability and waste control management. Image processing systems are new and …
their marketability and waste control management. Image processing systems are new and …
Deep learning based HEp-2 image classification: A comprehensive review
Classification of HEp-2 cell patterns plays a significant role in the indirect
immunofluorescence test for identifying autoimmune diseases in the human body. Many …
immunofluorescence test for identifying autoimmune diseases in the human body. Many …
Classification of pulmonary CT images by using hybrid 3D-deep convolutional neural network architecture
H Polat, H Danaei Mehr - Applied Sciences, 2019 - mdpi.com
Lung cancer is the most common cause of cancer-related deaths worldwide. Hence, the
survival rate of patients can be increased by early diagnosis. Recently, machine learning …
survival rate of patients can be increased by early diagnosis. Recently, machine learning …
Machine Learning and Feature Selection Methods for EGFR Mutation Status Prediction in Lung Cancer
The evolution of personalized medicine has changed the therapeutic strategy from classical
chemotherapy and radiotherapy to a genetic modification targeted therapy, and although …
chemotherapy and radiotherapy to a genetic modification targeted therapy, and although …
Intelligent scheduling with reinforcement learning
In this paper, we present and discuss an innovative approach to solve Job Shop scheduling
problems based on machine learning techniques. Traditionally, when choosing how to solve …
problems based on machine learning techniques. Traditionally, when choosing how to solve …
Adaptive aggregated attention network for pulmonary nodule classification
K Xia, J Chi, Y Gao, Y Jiang, C Wu - Applied Sciences, 2021 - mdpi.com
Lung cancer has one of the highest cancer mortality rates in the world and threatens
people's health. Timely and accurate diagnosis can greatly reduce the number of deaths …
people's health. Timely and accurate diagnosis can greatly reduce the number of deaths …
Performance of fine-tuning convolutional neural networks for HEP-2 image classification
The search for anti-nucleus antibodies (ANA) represents a fundamental step in the
diagnosis of autoimmune diseases. The test considered the gold standard for ANA research …
diagnosis of autoimmune diseases. The test considered the gold standard for ANA research …
Virtual world as an interactive safety training platform
Virtual training platform allows interactive and engaging learning through practice without
exposing trainees to hazards. In the recent pandemic (COVID-19) situation, online training is …
exposing trainees to hazards. In the recent pandemic (COVID-19) situation, online training is …
Gradient-guided convolutional neural network for MRI image super-resolution
X Du, Y He - Applied Sciences, 2019 - mdpi.com
Super-resolution (SR) technology is essential for improving image quality in magnetic
resonance imaging (MRI). The main challenge of MRI SR is to reconstruct high-frequency …
resonance imaging (MRI). The main challenge of MRI SR is to reconstruct high-frequency …