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A novel deep learning method for detection and classification of plant diseases
The agricultural production rate plays a pivotal role in the economic development of a
country. However, plant diseases are the most significant impediment to the production and …
country. However, plant diseases are the most significant impediment to the production and …
[HTML][HTML] Detection of diabetic eye disease from retinal images using a deep learning based CenterNet model
Diabetic retinopathy (DR) is an eye disease that alters the blood vessels of a person
suffering from diabetes. Diabetic macular edema (DME) occurs when DR affects the macula …
suffering from diabetes. Diabetic macular edema (DME) occurs when DR affects the macula …
Artificial intelligence-based drone system for multiclass plant disease detection using an improved efficient convolutional neural network
The role of agricultural development is very important in the economy of a country. However,
the occurrence of several plant diseases is a major hindrance to the growth rate and quality …
the occurrence of several plant diseases is a major hindrance to the growth rate and quality …
Melanoma segmentation: A framework of improved DenseNet77 and UNET convolutional neural network
Melanoma is the most fatal type of skin cancer which can cause the death of victims at the
advanced stage. Extensive work has been presented by the researcher on computer vision …
advanced stage. Extensive work has been presented by the researcher on computer vision …
[HTML][HTML] Swin-transformer-based YOLOv5 for small-object detection in remote sensing images
X Cao, Y Zhang, S Lang, Y Gong - Sensors, 2023 - mdpi.com
This study aimed to address the problems of low detection accuracy and inaccurate
positioning of small-object detection in remote sensing images. An improved architecture …
positioning of small-object detection in remote sensing images. An improved architecture …
CXray-EffDet: chest disease detection and classification from X-ray images using the EfficientDet model
The competence of machine learning approaches to carry out clinical expertise tasks has
recently gained a lot of attention, particularly in the field of medical-imaging examination …
recently gained a lot of attention, particularly in the field of medical-imaging examination …
Arabic handwritten recognition using deep learning: A survey
N Alrobah, S Albahli - Arabian Journal for Science and Engineering, 2022 - Springer
In recent times, many research projects and experiments target machines that automatically
recognize handwritten characters, but most of them are done in Latin. Recognizing …
recognize handwritten characters, but most of them are done in Latin. Recognizing …
Copy move forgery detection and segmentation using improved mask region-based convolution network (RCNN)
Copy-move forgery (CMF) is a common image manipulation approach that uses the
information from the same sample to manipulate it with the intent of hiding the required …
information from the same sample to manipulate it with the intent of hiding the required …
DCNet: DenseNet-77-based CornerNet model for the tomato plant leaf disease detection and classification
Early recognition of tomato plant leaf diseases is mandatory to improve the food yield and
save agriculturalists from costly spray procedures. The correct and timely identification of …
save agriculturalists from costly spray procedures. The correct and timely identification of …
[HTML][HTML] Analysis of brain MRI images using improved cornernet approach
The brain tumor is a deadly disease that is caused by the abnormal growth of brain cells,
which affects the human blood cells and nerves. Timely and precise detection of brain …
which affects the human blood cells and nerves. Timely and precise detection of brain …