PROJECT TITLE :

Text-Attentional Convolutional Neural Network for Scene Text Detection

ABSTRACT:

Recent deep learning models have demonstrated strong capabilities for classifying text and non-text parts in natural images. They extract a high-level feature globally computed from a full image element (patch), where the cluttered background information may dominate true text features in the deep representation. This leads to less discriminative power and poorer robustness. During this paper, we gift a new system for scene text detection by proposing a unique text-attentional convolutional neural network (Text-CNN) that significantly focuses on extracting text-related regions and options from the image elements. We have a tendency to develop a replacement learning mechanism to train the Text-CNN with multi-level and rich supervised information, together with text region mask, character label, and binary text/non-text data. The made supervision information enables the Text-CNN with a strong capability for discriminating ambiguous texts, and also will increase its robustness against difficult background parts. The coaching process is formulated as a multi-task learning problem, where low-level supervised information greatly facilitates the most task of text/non-text classification. Additionally, a strong low-level detector known as contrast-enhancement maximally stable extremal regions (MSERs) is developed, that extends the widely used MSERs by enhancing intensity distinction between text patterns and background. This permits it to detect highly difficult text patterns, resulting in an exceedingly higher recall. Our approach achieved promising results on the ICDAR 2013 knowledge set, with an F-live of 0.82, substantially improving the state-of-the-art results.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE :Modeling, Detection, and Diagnosis of Faults in Multilevel Memristor MemoriesABSTRACT:Memristors are an attractive choice for use in future memory architectures but are vulnerable to high defect densities thanks
PROJECT TITLE : Video Dissemination over Hybrid Cellular and Ad Hoc Networks - 2014 ABSTRACT: We study the problem of disseminating videos to mobile users by using a hybrid cellular and ad hoc network. In particular, we formulate
PROJECT TITLE : Sleep Scheduling for Geographic Routing in Duty-Cycled Mobile Sensor Network - 2014 ABSTRACT: Recently, the research focus on geographic routing, a promising routing scheme in wireless sensor networks (WSNs),
PROJECT TITLE : Security Analysis of Handover Key Management in 4G LTESAE Networks - 2014 ABSTRACT: The goal of 3GPP Long Term Evolution/System Architecture Evolution (LTE/SAE) is to move mobile cellular wireless technology
PROJECT TITLE : PSR A Lightweight Proactive Source Routing Protocol For Mobile Ad Hoc Networks - 2014 ABSTRACT: Opportunistic data forwarding has drawn much attention in the research community of multihop wireless networking,

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry