[HTML][HTML] A leaf image localization based algorithm for different crops disease classification

Y Kurmi, S Gangwar - Information processing in agriculture, 2022 - Elsevier
Agricultural crop production is a major contributing element to any country's economy. To
maintain the economic growth of any country plants disease detection is a leading factor in …

Deep CNN model for crops' diseases detection using leaf images

Y Kurmi, P Saxena, BS Kirar, S Gangwar… - … Systems and Signal …, 2022 - Springer
The agricultural yield of any country provides the base for the development of that nation.
Sustainable growth needs to maintain crop production up to a certain level that depends on …

Brain tumour detection in magnetic resonance imaging using Levenberg–Marquardt backpropagation neural network

M Ghahramani, N Shiri - IET image processing, 2023 - Wiley Online Library
Magnetic resonance imaging (MRI) is a high‐quality medical image that is used to detect
brain tumours in a complex and time‐consuming manner. In this study, a back propagation …

Leaf images classification for the crops diseases detection

Y Kurmi, S Gangwar, V Chaurasia, A Goel - Multimedia Tools and …, 2022 - Springer
Crop production affects the economy of a specific region or country. To maintain the
economic development of any territory crops disease detection is a leading factor in …

Brain MRI detection and classification: Harnessing convolutional neural networks and multi-level thresholding

RR Kamireddy, RN Kandala, R Dhuli, S Polinati… - Plos one, 2024 - journals.plos.org
Brain tumor detection in clinical applications is a complex and challenging task due to the
intricate structures of the human brain. Magnetic Resonance (MR) imaging is widely …

[PDF][PDF] A Hybrid Deep CNN-SVM Approach for Brain Tumor Classification.

A Biswas, MS Islam - Journal of Information Systems Engineering …, 2023 - researchgate.net
Background: Feature extraction process is noteworthy in order to categorize brain tumors.
Handcrafted feature extraction process consists of profound limitations. Similarly, without …

Content-based image retrieval algorithm for nuclei segmentation in histopathology images: CBIR algorithm for histopathology image segmentation

Y Kurmi, V Chaurasia - Multimedia Tools and Applications, 2021 - Springer
In today's world, the medical diagnostic system shows a high reliance on medical imagery
and digital nosology. To facilitate the fast and precise screening of samples, technology is …

Brain Tumor Categorization and Retrieval Using Deep Brain Incep Res Architecture Based Reinforcement Learning Network

J Chaki, M Woźniak - IEEE Access, 2023 - ieeexplore.ieee.org
The categorization and retrieval of brain tumors using Magnetic Resonance Imaging (MRI) is
a difficult but necessary process for brain tumor diagnosis. In this study, a reinforcement …

Optimization empowered hierarchical residual VGGNet19 network for multi-class brain tumour classification

PR Krishna, V Prasad, TK Battula - Multimedia Tools and Applications, 2023 - Springer
Brain tumour is a fatal disease and its diagnosis is a difficult procedure for radiologists due
to the heterogeneous behaviour of tumour cells. Diagnosing brain tumour using MRI at early …

Evolutionary gravitational neocognitron neural network optimized with marine predators optimization algorithm for MRI brain tumor classification

A Lakshmi, M Alagarsamy… - … Biology and Medicine, 2024 - Taylor & Francis
Magnetic resonance imaging (MRI) is a powerful tool for tumor diagnosis in human brain.
Here, the MRI images are considered to detect the brain tumor and classify the regions as …