Problems and Solutions in Semantic Segmentation: An Overview of DeepLabV1

This article explains the two main challenges of applying deep convolutional neural networks to semantic segmentation—signal down‑sampling and loss of spatial precision—and describes how the DeepLabV1 architecture, using dilated convolutions, large‑field‑of‑view modules, fully‑connected CRF and multi‑scale fusion, addresses these issues while achieving faster, more accurate segmentation results.

CRFDeepLabV1dilated convolution

0 likes · 12 min read

Problems and Solutions in Semantic Segmentation: An Overview of DeepLabV1

Python Programming Learning Circle

Jan 8, 2020 · Artificial Intelligence

How Dilated Convolutions Preserve Image Size While Expanding Receptive Field

This article explains the concept, mathematics, and practical PyTorch implementation of dilated (or atrous) convolutions, showing how to keep image dimensions unchanged while dramatically increasing the receptive field and discussing their advantages and typical applications.

Deep LearningImage ProcessingPyTorch

0 likes · 4 min read

How Dilated Convolutions Preserve Image Size While Expanding Receptive Field

Alibaba Cloud Developer

Mar 6, 2019 · Artificial Intelligence

How Deep Learning Unwarps Curved Document Images for Better OCR

This article explores how deep‑learning‑based image dewarping techniques, from traditional hardware methods to modern U‑Net, Stacked U‑Net and Dilated U‑Net architectures, can correct warped document photos, improve OCR accuracy, and support intelligent verification in high‑throughput business scenarios.

Deep LearningModel EvaluationOCR

0 likes · 19 min read

How Deep Learning Unwarps Curved Document Images for Better OCR

Alibaba Cloud Developer

Sep 25, 2018 · Artificial Intelligence

How Deep Learning Unwarps Curved Document Images for Better OCR

This article explores the challenges of OCR on warped document images, reviews traditional and deep‑learning‑based correction methods, describes a synthetic dataset generation pipeline, proposes enhanced U‑Net architectures including stacked and dilated variants, evaluates them with MS‑SSIM, and outlines future research directions.

Deep LearningOCRU-Net

0 likes · 18 min read

Alibaba Cloud Developer

Jul 6, 2018 · Artificial Intelligence

How Dynamic Scale Selection Boosts Real-Time Action Prediction

This article explains online action prediction, the challenges of early‑stage classification, and introduces a Scale Selection Network that dynamically chooses optimal temporal windows using dilated convolutions, regression and classification sub‑networks, achieving state‑of‑the‑art results on two benchmark datasets.

Computer VisionDeep Learningdilated convolution

0 likes · 7 min read

How Dynamic Scale Selection Boosts Real-Time Action Prediction