Ensemble of Visual Transformer and Deep Neural Networks for Recognizing Sunflower Diseases from Photographs

Ensemble of Visual Transformer and Deep Neural Networks for Recognizing Sunflower Diseases from Photographs

The world's population is growing steadily, but already more than 1.5 billion people are experiencing acute food shortages. Oilseeds, such as sunflower, are important sources of vegetable fat and contain large amounts of calories, amino acids, vitamin D, minerals and antioxidants, making them e...

Tallennettuna:

Bibliografiset tiedot
Päätekijät:	Baboshina, V. A., Бабошина, В. А., Lyakhov, P. A., Ляхов, П. А.
Aineistotyyppi:	Статья
Kieli:	English
Julkaistu:	Springer Science and Business Media Deutschland GmbH 2024
Aiheet:	Deep neural network Visual transformer Sunflower diseases Patch recognition Ensemble neural network
Linkit:	https://dspace.ncfu.ru/handle/123456789/29157
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

Samankaltaisia teoksia

Bidirectional Encoder representation from Image Transformers for recognizing sunflower diseases from photographs
Tekijä: Baboshina, V. A., et al.
Julkaistu: (2025)

Multimodal ensemble neural network system for skin cancer detection on heterogeneous dermatological data
Tekijä: Lyakhova, U. A., et al.
Julkaistu: (2024)

Neural Network System for Recognizing Images Affected by Random-Valued Impulse Noise
Tekijä: Orazaev, A. R., et al.
Julkaistu: (2023)

Neural network recognition system for video transmitted through a binary symmetric channel
Tekijä: Baboshina, V. A., et al.
Julkaistu: (2024)

Detection of attention state in children with autism spectrum disorder based on neural network classification of electroencephalograms
Tekijä: Lyakhov, P. A., et al.
Julkaistu: (2025)

Neural network technologies in economics study aid
Tekijä: Kovalenko, A. V.

Analysis of an Existing Method for Detecting Adversarial Attacks on Deep Neural Networks
Tekijä: Lapina, M. A., et al.
Julkaistu: (2024)

Hardware and software implementation of neural network control of power systems based on the system of residual classes
Tekijä: Tikhonov, E. E., et al.
Julkaistu: (2020)

Machine Learning Research Methods for Identifying Inaccurate Content
Tekijä: Lapina, M. A., et al.
Julkaistu: (2025)

Development of forecasting theory and methods for developing forecasts in electroenergetics
Tekijä: Tikhonov, E. E., et al.
Julkaistu: (2021)

Fault Tolerant System for Data Storage, Transmission and Processing in Fog Computing Using Artificial Neural Networks
Tekijä: Lutsenko, V. V., et al.
Julkaistu: (2024)

Development of prognostic neural network models based on non-positional coding for automatic control systems
Tekijä: Tikhonov, E. E., et al.
Julkaistu: (2019)

Development of an Approach to Confidential Learning with Errors in the Design of Neural Networks
Tekijä: Bezuglova, E. S., et al.
Julkaistu: (2024)

The Possibilities of Using Neural Networks in Literature Lessons at School
Tekijä: Murashko, E. I., et al.
Julkaistu: (2024)

Multirecurrent Neural Network in Discrete Form
Tekijä: Shaposhnikov, A. V., et al.
Julkaistu: (2024)

Analytical Review of Classification and Clustering Methods of Cyber Attacks Based on Data Mining and Neural Network Approach
Tekijä: Fedina, A. D., et al.
Julkaistu: (2024)

Physics-informed neural network model using natural gradient descent with Dirichlet distribution
Tekijä: Abdulkadirov, R. I., et al.
Julkaistu: (2025)

Perceptions of Neural Network Use in Higher Education: Case Study
Tekijä: Yesayan, M. L., et al.
Julkaistu: (2025)

An Approximate Algorithm for Determining the Sign Function of a Number Using Neural Network Methods
Tekijä: Shiriaev, E. M., et al.
Julkaistu: (2024)

Enhancing Cloud Security through Efficient Polynomial Approximations for Homomorphic Evaluation of Neural Network Activation Functions
Tekijä: Babenko, M. G., et al.
Julkaistu: (2024)

Artificial Intelligence in Education and Training
Tekijä: Sidin, M. G., et al.
Julkaistu: (2025)

Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
Tekijä: Lutsenko, V. V., et al.
Julkaistu: (2024)

Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers
Tekijä: Abdulkadirov, R. I., et al.
Julkaistu: (2025)

High-Speed Convolution Core Architecture for Privacy-Preserving Neural Networks
Tekijä: Lapina, M. A., et al.
Julkaistu: (2024)

Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent
Tekijä: Abdulkadirov, R. I., et al.
Julkaistu: (2024)

Recognition of Particle Impacts in Acoustic Fixing of Dust Flow Using an Artificial Neural Network
Tekijä: Valuev, G. V., et al.
Julkaistu: (2024)

Physics-Aware Machine Learning Approach for High-Precision Quadcopter Dynamics Modeling
Tekijä: Abdulkadirov, R. I., et al.
Julkaistu: (2025)

Методы и модели исследования сложных систем и обработки больших данных монография
Tekijä: Парамонов И. Ю.
Julkaistu: (2020)

Методы и модели исследования сложных систем и обработки больших данных монография
Tekijä: Парамонов И. Ю.
Julkaistu: (2024)

Implementation of CMAC neural network control systems in residue number system
Tekijä: Koldaev, A. I., et al.
Julkaistu: (2020)

Methodology and Technology of Using Neural Networks in Agriculture
Tekijä: Mikhailov, G. G., et al.
Julkaistu: (2024)

Enhancing Drone Detection via Transformer Neural Network and Positive–Negative Momentum Optimizers
Tekijä: Lyakhov, P. A., et al.
Julkaistu: (2025)

Main hereditary diseases and anomalies in farm animals study aid
Tekijä: Maksimov, G. V.

Application of Information Technologies in the Development and Implementation of Educational Programmes in the Field of Media Communications
Tekijä: Ezhova, E. N., et al.
Julkaistu: (2025)

Data Control in Distributed Self-organizing Sensor Network Under Speciffic Deployment Condition
Tekijä: Lapina, M. A., et al.
Julkaistu: (2024)

Online Teaching of Students of Pedagogical Courses by Teachers from Abroad
Tekijä: Konopko, E. A., et al.
Julkaistu: (2025)

Propaedeutics of internal diseases: methods of examination of the patient textbook

Методы инспекции пакетов и анализа трафика. Технология Deep Packet Inspection учебно-методическое пособие
Tekijä: Гольдштейн Б. С.
Julkaistu: (2018)

Big Data study aid
Tekijä: Cheremukhin, A. D.

Comparative Analysis and Development of Recommendations for the Use of Machine Learning Methods to Identify Network Traffic Anomalies in the Development of a Subsystem for User Behavioral Analysis
Tekijä: Govorova, S. V., et al.
Julkaistu: (2024)