Daniil Komov
VERIFIED TECHNICAL DOSSIERSources checked

Daniil Komov

Computer Vision Lead

2 Verified ArtifactsSource Checked & Attributed

Verified Proof of Work Artifacts

2 items cataloged

Each artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Daniil Komov. Every entry undergoes editorial source verification.

#1
IMPLEMENTATION Checked Sep 20, 2026

Web-Based Deep Learning Model Training and Annotation Platform

Architected a cloud-based platform enabling non-technical users to annotate images with bounding boxes, polygons, and keypoints, and train custom classification, object detection, and OCR models with one click.

Model & Execution Context:PyTorch, ONNX Runtime, WebSockets for live training metrics, automated augmentations.
Scope & Limitations

Training speed depends on GPU cluster queue availability during peak multi-user training workloads.

#2
IMPLEMENTATION Checked Sep 20, 2026

High-Speed Optical Character Recognition and Table Extraction Engine

Developed an end-to-end OCR and table structure recognition engine capable of processing warped or skewed scans at under 100ms per page with 98.7% character accuracy across Latin and Cyrillic scripts.

Model & Execution Context:Convolutional recurrent neural network (CRNN) with CTC loss, line segmentation heuristics.
Scope & Limitations

Heavily degraded handwritten documents require specialized handwriting transformer (HTR) checkpoints.