Elena Limonova
МФТИ
- Neural Networks and Applications
- Advanced Image and Video Retrieval Techniques
- Handwritten Text Recognition Techniques
- Advanced Neural Network Applications
- Image Retrieval and Classification Techniques
Чем занимается
Ключевые темы по публикациям: Neural Networks and Applications; Advanced Image and Video Retrieval Techniques; Handwritten Text Recognition Techniques; Advanced Neural Network Applications; Image Retrieval and Classification Techniques.
Последние работы
Все 54 в OpenAlexConvolutional Neural Network Structure Transformations for Complexity Reduction and Speed Improvement2018 · аннотациясвернуть
Two methods of convolution-complexity reduction, and therefore acceleration of convolutional neural network processing, are introduced. Convolutional neural networks (CNNs) are widely used in computer vision problems.…
Bipolar Morphological Neural Networks: Gate-Efficient Architecture for Computer Vision2021 · аннотациясвернуть
The priority of building hardware-oriented neural network models is growing steadily. The target goals for their development are the performance and energy efficiency of promising hardware-software solutions.…
p-im2col: Simple Yet Efficient Convolution Algorithm With Flexibly Controlled Memory Overhead2021 · аннотациясвернуть
Convolution is the most time-consuming operation in modern deep artificial neural networks, so its performance is crucial for fast inference. One of the standard approaches to fast convolution computation is to use…
- Combining convolutional neural networks and Hough Transform for classification of images containing lines2017
- Fast Gaussian Filter Approximations Comparison on SIMD Computing Platforms2024
- Universal Comparison Methodology for Hough Transform Approaches2026
- Fast approximate matrix multiplication for 8-bit neural networks using tree averaging2026
- Fast- and memory-efficient convolution on ARM for computer vision neural networks2026
Наукометрия
Написать научруку
Email не найден в открытых источниках — поищи на странице вуза или в последних статьях.
Шаблон письма
Здравствуйте, Elena Limonova! Я студент(ка) [курс, факультет, вуз]. Мне интересна тема [опишите интересы своими словами]. Прочитал(а) вашу работу «Convolutional Neural Network Structure Transformations for Complexity Reduction and Speed Improvement» (2018) — она близка к тому, чем я хочу заниматься. Хочу обсудить возможность выполнить научную работу под вашим руководством. Буду благодарен(на) за ответ — готов(а) рассказать о себе подробнее и прислать резюме. С уважением, [Имя Фамилия]
На этапе теста письмо отправляешь сам из своей почты. Отправка из сервиса и статусы заявок — скоро.