A survey of uncertainty in deep neural networks
Over the last decade, neural networks have reached almost every field of science and
become a crucial part of various real world applications. Due to the increasing spread …
become a crucial part of various real world applications. Due to the increasing spread …
Deep learning in photoacoustic imaging: a review
Significance: Photoacoustic (PA) imaging can provide structural, functional, and molecular
information for preclinical and clinical studies. For PA imaging (PAI), non-ideal signal …
information for preclinical and clinical studies. For PA imaging (PAI), non-ideal signal …
The class imbalance problem in deep learning
Deep learning has recently unleashed the ability for Machine learning (ML) to make
unparalleled strides. It did so by confronting and successfully addressing, at least to a …
unparalleled strides. It did so by confronting and successfully addressing, at least to a …
DCGAN-based data augmentation for tomato leaf disease identification
Tomato leaf disease seriously affects the yield of tomato. It is extremely vital for agricultural
economy to identify agricultural diseases. The traditional data augmentation methods, such …
economy to identify agricultural diseases. The traditional data augmentation methods, such …
Tomato leaf disease diagnosis based on improved convolution neural network by attention module
S Zhao, Y Peng, J Liu, S Wu - Agriculture, 2021 - mdpi.com
Crop disease diagnosis is of great significance to crop yield and agricultural production.
Deep learning methods have become the main research direction to solve the diagnosis of …
Deep learning methods have become the main research direction to solve the diagnosis of …
Maize leaf disease identification based on feature enhancement and DMS-robust alexnet
M Lv, G Zhou, M He, A Chen, W Zhang, Y Hu - IEEE access, 2020 - ieeexplore.ieee.org
The identification of maize leaf diseases will meet great challenges because of the
difficulties in extracting lesion features from the constant-changing environment, uneven …
difficulties in extracting lesion features from the constant-changing environment, uneven …
Target discrimination, concentration prediction, and status judgment of electronic nose system based on large-scale measurement and multi-task deep learning
Pattern recognition is the core component of the electronic nose (E-nose). Traditional
machine learning algorithms highly rely on the feature data selected manually for model …
machine learning algorithms highly rely on the feature data selected manually for model …
基于改进Multi-Scale AlexNet 的番茄叶部病害图像识别.
郭小清， 范涛杰， 舒欣 - … of the Chinese Society of Agricultural …, 2019 - search.ebscohost.com
番茄同种病害在不同发病阶段表征差异明显, 不同病害又表现出一定的相似性,
传统模式识别方法不能体现病害病理表征的动态变化, 实用性较差. 针对该问题 …
传统模式识别方法不能体现病害病理表征的动态变化, 实用性较差. 针对该问题 …
Apple leaf disease identification via improved CycleGAN and convolutional neural network
The identification of apple leaf diseases is crucial to reduce yield reduction and timely take
disease control measures. Employing deep learning for apple leaf disease identification is …
disease control measures. Employing deep learning for apple leaf disease identification is …
Steering or braking avoidance response in SHRP2 rear-end crashes and near-crashes: A decision tree approach
A Sarkar, JS Hickman, AD McDonald, W Huang… - Accident Analysis & …, 2021 - Elsevier
Objective The paper presents a systematic analysis of drivers' crash avoidance response
during crashes and near-crashes and developed a machine learning-based predictive …
during crashes and near-crashes and developed a machine learning-based predictive …