Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Mechanical Engineering
11
Scopus Publications
Scopus Publications
Automatic Polygon Annotation of Plant Objects for Training Dataset Preparation in Green Biomass Segmentation Tasks Evgeniy Ivliev, Valery Gvindjiliya, Danila Donskoy, Yevgeniy Chayka Journal of Imaging, 2026 This paper addresses the problem of automated segmentation of plant green biomass in field crop images aimed at improving the accuracy of crop and weed identification. To construct a training dataset for neural network models, an automatic annotation algorithm is proposed, enabling the generation of polygonal object masks without human intervention. The method is based on adaptive analysis of color characteristics of plant fragments with iterative narrowing of the hue range in the HSV color space, combined with an integral quality metric that accounts for the dynamics of contour area and shape. The proposed method achieved an IoU of 93.22% and a DSC of 96.30%, demonstrating a high level of agreement between automatic and manual annotations. The generated masks are used to train segmentation models of the YOLO11-seg family. Models of different scales (n, s, m, l, x) were trained and evaluated using standard metrics, including Intersection over Union (IoU), mAP@0.5, mAP@0.5–0.95, F1-score, and Precision–Recall (PR) curves. Experimental results demonstrate that models trained on automatically generated annotations achieve stable segmentation performance of plant green biomass. The best results were obtained with the YOLO11m-seg model, achieving an F1-score of 0. 772. The results confirm the effectiveness of the proposed approach and demonstrate acceptable segmentation quality, supported by both quantitative metrics and visual analysis. The developed automatic annotation algorithm can be used to expand training datasets in computer vision tasks for agricultural applications.
TinyML Classification for Agriculture Objects with ESP32 Danila Donskoy, Valeria Gvindjiliya, Evgeniy Ivliev Digital, 2025 Using systems with machine learning technologies for process automation is a global trend in agriculture. However, implementing this technology comes with challenges, such as the need for a large amount of computing resources under conditions of limited energy consumption and the high cost of hardware for intelligent systems. This article presents the possibility of applying a modern ESP32 microcontroller platform in the agro-industrial sector to create intelligent devices based on the Internet of Things. CNN models are implemented based on the TensorFlow architecture in hardware and software solutions based on the ESP32 microcontroller from Espressif company to classify objects in crop fields. The purpose of this work is to create a hardware–software complex for local energy-efficient classification of images with support for IoT protocols. The results of this research allow for the automatic classification of field surfaces with the presence of “high attention” and optimal growth zones. This article shows that classification accuracy exceeding 87% can be achieved in small, energy-efficient systems, even for low-resolution images, depending on the CNN architecture and its quantization algorithm. The application of such technologies and methods of their optimization for energy-efficient devices, such as ESP32, will allow us to create an Intelligent Internet of Things network.
Load and Positional Constraints’ Impact on the Accuracy and Dynamic Performance of an Autonomous Adaptive Electrohydraulic Pump-Controlled Actuator for Mobile Equipment Alexey N. Beskopylny, Evgeniy Ivliev, Vyacheslav Grishchenko, Denis Medvedev Actuators, 2025 This study investigates the external load and positional constraints’ impact on the accuracy and performance of an autonomous adaptive electrohydraulic actuator with pump control intended for mobile equipment. An actuator simulation model was developed in the MATLAB/Simulink (version R2021A) environment, and a full-scale experimental setup was constructed to validate this model. Various motion trajectories under different load conditions were analyzed to evaluate discrepancies between simulated and experimental results and to identify key performance characteristics across operational modes. The results demonstrate that the simulation model adequately replicates the actuator’s dynamic behavior, although deviations emerge under high-load conditions. Notably, in the absence of external load, the static positioning error does not exceed 0.025 mm (0.05% of the 50 mm target value), while under the maximum load of 8000 N, the error increases to 0.075 mm (0.15% of the 50 mm target value). These limitations are primarily due to current constraints imposed by the actuator’s power supply capacity (up to 300 W at 24 V), which restrict pressure buildup rates under heavy loads. Nevertheless, the proposed control system exhibits robustness to load variations and ensures positioning accuracy within acceptable limits, demonstrating its practical suitability for mobile machinery applications. The developed simulation model also serves as a valuable tool for control system tuning and testing in the absence of a physical prototype.
Development of a Small-Working-Volume Plunger Hydraulic Pump with Improved Performance Characteristics Alexey N. Beskopylny, Denis Medvedev, Vyacheslav Grishchenko, Evgeniy Ivliev Actuators, 2025 Current trends in the development of technology are linked inextricably to the increasing level of automation in technological processes and production systems. In this regard, the development of systems for supplying working fluids with adjustable pumps that have high performance characteristics, an increased service life and low operating costs is an important scientific and technical task. A primary challenge in the development of such systems lies in achieving low fluid flow rates while maintaining stable operating characteristics. This challenge stems from the fact that currently available controlled hydraulic pumps exhibit either a high cost or suboptimal life and efficiency parameters. This work focuses on the development of a plunger hydraulic pump with a small working volume. A mathematical model has been developed to investigate the characteristics, optimize the design of this pump and further expand the size range of such pumps. The solution was implemented on a computer using the dynamic modelling environment MATLAB/Simulink. In order to verify the mathematical model’s adequacy, a plunger pump prototype was built and integrated with a test bench featuring a measurement system. The test results showed higher pump efficiency and a significant reduction in hydraulic losses. An analysis of the obtained data shows that the pump is characterized by increased efficiency due to optimal flow distribution and reduced internal leakage, which makes it promising for use in hydraulic systems requiring improved operating characteristics. The developed pump has more rational characteristics compared to existing alternatives for use in water supply systems for induction superheaters. The experimental external characteristics of the developed pump are 10% higher than the external characteristics of the ULKA EX5 pump selected as an analogue, and the pressure characteristics are 65% higher. It offers production costs that are several times lower compared to existing cam-type plunger or diaphragm pumps with oil sumps and precision valve mechanisms. Additionally, it has significantly better operating characteristics and a longer service life compared to vibrating plunger pumps.
Analysis of the vehicle's flow based on the neural network and the SIFT method Victor Ivliev, Evgeniy Ivliev, Pavel Obukhov, Alexander Obukhov Bio Web of Conferences, 2024 The article presents a vehicle counting system based on TensorFlow neural network models and the SIFT machine vision method. An experimental comparison was made of five detectors consisting of metaarchitecture (Faster R-CNN, SSD) and neural networks extracting features (Resnet V1 100, Inception V2, Inception Resnet V2 and Mobilenet V1). The main aspects of these detectors are analyzed, such as accuracy, speed, memory consumption, the number of floating point operations per second and the number of trainable parameters of convolutional neural networks. The calculation of vehicles is carried out by an algorithm based on the SIFT method. This algorithm compares the descriptors of all vehicles in the frame at the current time with the descriptors at the previous time. Based on the maximum match of the descriptors, the algorithm assigns the vehicle identification number from the previous frame, and in the absence of matches creates a new identification number. This approach will make it possible to calculate vehicles more accurately and assess their trajectory and speed.
Improving the energy efficiency of sorting centers by identifying objects and digit-letter information with neural networks Evgeniy Ivliev, Pavel Obukhov, Viktor Ivliev, Denis Medvedev, Viktor Martynov E3s Web of Conferences, 2021 The article is devoted to the development and analysis of methods of identifying dynamic objects. A neural network with the architecture of SSD MobileNetV2 has been developed to solve the problem of detecting baggage tags and barcodes. Several approaches are considered to solve the problem of identifying digital-letter information: Tesseract, SSD InceptionV2, OpenCV and a convolutional neural network. The efficiency of the methods on real images was checked. It was concluded that electricity consumption can be reduced by 49.43%.
Mathematical model of the pneumatic actuator follower system Denis Medvedev, Vyacheslav Grishhenko, Viktor Martynov, Evgeniy Ivliev, Yurii Korol’kov E3s Web of Conferences, 2021 The article considers a method of controlling the motion of the output links of the tracking system of pneumatic actuators of technological equipment actuators. Dynamic and qualitative characteristics are improved by means of proportional-integral-differential (PID) controller. The mathematical model of actuator system, which includes power and control parts, has been developed. By calculation experiment the dynamic characteristics of the actuator have been obtained, from which it has been found possible to reduce the energy consumed by the actuator system to about 30%.
