RGB-T Salient Object Detection via Fusing Multi-Level CNN Features


Deep convolutional neural networks have lately made significant progress in the field of RGB-inducing salient object recognition (CNNs). The problem is that these detections have to contend with a wide range of tough situations that include low-light circumstances, varying light levels, and crowded backdrops. Instead of trying to improve RGB-based saliency detection, this research takes advantage of the complementing advantages of RGB and thermal infrared images. A novel end-to-end network for multi-modal salient object recognition is proposed, which turns the challenge of RGB-T saliency detection into a CNN feature-fusion issue. An initial backbone network is used to extract coarse features from each RGB or thermal infrared image, and then several ADFC modules are designed to extract multi-level refined features for each single-modal input image, taking into account that features captured at different depths differ in semantic information and visual details. Additionally, the cross-modal features from a pair of RGB-T images are combined using an MGF module, which utilises the ADFC modules for each level. As a final step, a joint attention guided bi-directional message passing (JABMP) module integrates the multi-level fused features from MGF modules to forecast saliency. Public RGB-T salient object datasets show that our proposed algorithm outperforms current state-of-the art algorithms in tough settings such as low contrast lighting and complex background conditions.

Did you like this research project?

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

PROJECT TITLE :Road Traffic Speed Prediction: A Probabilistic Model Fusing Multi-Source Data - 2018ABSTRACT:Road traffic speed prediction could be a difficult downside in intelligent transportation system (ITS) and has gained
PROJECT TITLE :A New Measure for Analyzing and Fusing Sequences of ObjectsABSTRACT:This work is related to the combinatorial information analysis downside of seriation used for data visualization and exploratory analysis. Seriation
PROJECT TITLE :Local Multimodal Serial Analysis for Fusing EEG-fMRI: A New Method to Study Familial Cortical Myoclonic Tremor and EpilepsyABSTRACT:Integrating information of neuroimaging multimodalities, like electroencephalography
PROJECT TITLE :The Data Context Map: Fusing Data and Attributes into a Unified DisplayABSTRACT:Various strategies have been described that permit the visualization of the data matrix. However all suffer from a standard downside
PROJECT TITLE :Ranking on Data Manifold with Sink Points - 2013ABSTRACT:Ranking is an important problem in various applications, such as Information Retrieval (IR), natural language processing, computational biology, and social

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

Project Enquiry