Review on convolutional neural network (CNN) applied to plant leaf disease classification
J Lu, L Tan, H Jiang - Agriculture, 2021 - mdpi.com
Crop production can be greatly reduced due to various diseases, which seriously endangers
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …
Infrared machine vision and infrared thermography with deep learning: A review
Infrared imaging-based machine vision (IRMV) is the technology used to automatically
inspect, detect, and analyse infrared images (or videos) obtained by recording the intensity …
inspect, detect, and analyse infrared images (or videos) obtained by recording the intensity …
Thermal-based early breast cancer detection using inception V3, inception V4 and modified inception MV4
Breast cancer is one of the most significant causes of death for women around the world.
Breast thermography supported by deep convolutional neural networks is expected to …
Breast thermography supported by deep convolutional neural networks is expected to …
A deep learning approach for automatic detection, segmentation and classification of breast lesions from thermal images
Purpose This study investigates implementation of deep learning (DL) approaches to breast
tumor recognition based on thermal images. We propose to utilize Mask R-CNN technique …
tumor recognition based on thermal images. We propose to utilize Mask R-CNN technique …
A systematic review of breast cancer detection using thermography and neural networks
MAS Al Husaini, MH Habaebi, SA Hameed… - IEEE …, 2020 - ieeexplore.ieee.org
Breast cancer plays a significant role in affecting female mortality. Researchers are actively
seeking to develop early detection methods of breast cancer. Several technologies …
seeking to develop early detection methods of breast cancer. Several technologies …
Automated detection of subsurface defects using active thermography and deep learning object detectors
DG Lema, OD Pedrayes… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The need for improved quality control in industry makes object detection crucial. This work
addresses the challenging problem of subsurface defect detections using a combination of …
addresses the challenging problem of subsurface defect detections using a combination of …
DRD-UNet, a UNet-like architecture for multi-class breast cancer semantic segmentation
Staining of histological slides with Hematoxylin and Eosin is widely used in clinical and
laboratory settings as these dyes reveal nuclear structures as well as cytoplasm and …
laboratory settings as these dyes reveal nuclear structures as well as cytoplasm and …
Efficient extraction of deep image features using a convolutional neural network (CNN) for detecting ventricular fibrillation and tachycardia
To safely select the proper therapy for ventricular fibrillation (VF), it is essential to distinguish
it correctly from ventricular tachycardia (VT) and other rhythms. Provided that the required …
it correctly from ventricular tachycardia (VT) and other rhythms. Provided that the required …
Transfer learning for breast cancer classification in terahertz and infrared imaging
M Gezimati, G Singh - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Proactive treatment of cancer, characterized by early detection and intervention is one of the
main focus of the next-generation healthcare systems for predictive, timely detection and …
main focus of the next-generation healthcare systems for predictive, timely detection and …
Integrating AI in NDE: Techniques, Trends, and Further Directions
E Pérez, CE Ardic, O Çakıroğlu, K Jacob… - arXiv preprint arXiv …, 2024 - arxiv.org
The digital transformation is fundamentally changing our industries, affecting planning,
execution as well as monitoring of production processes in a wide range of application …
execution as well as monitoring of production processes in a wide range of application …