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Found 8 papers, 0 papers with code
CompTLL-UNet: Compressed Domain Text-Line Localization in Challenging Handwritten Documents using Deep Feature Learning from JPEG Coefficients
Automatic localization of text-lines in handwritten documents is still an open and challenging research problem.
T2CI-GAN: Text to Compressed Image generation using Generative Adversarial Network
The first model is directly trained with JPEG compressed DCT images (compressed domain) to generate the compressed images from text descriptions.
Document Image Binarization in JPEG Compressed Domain using Dual Discriminator Generative Adversarial Networks
Image binarization techniques are being popularly used in enhancement of noisy and/or degraded images catering different Document Image Anlaysis (DIA) applications like word spotting, document retrieval, and OCR.
HWRCNet: Handwritten Word Recognition in JPEG Compressed Domain using CNN-BiLSTM Network
Handwritten word recognition from document images using deep learning is an active research area in the field of Document Image Analysis and Recognition.
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique
Therefore accurate and timely detection of leaf disease is very important to check the loss of the crops and meet the growing food demand of the people.
Deep Learning Based Image Retrieval in the JPEG Compressed Domain
Here, we propose a unified model for image retrieval which takes DCT coefficients as input and efficiently extracts global and local features directly in the JPEG compressed domain for accurate image retrieval.
Automatic Text Line Segmentation Directly in JPEG Compressed Document Images
The first approach is based on the strategy of partial decompression of selected DCT blocks, and the second approach is with intelligent analysis of F10 and F11 AC coefficients and without using any type of decompression.
DCT-CompCNN: A Novel Image Classification Network Using JPEG Compressed DCT Coefficients
However, if we intend to classify images directly with its compressed data, the same approach may not work better, like in case of JPEG compressed images.
