An empirical review of deep learning frameworks for change detection: Model design, experimental frameworks, challenges and research needs
M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …
background regions, is one of the elementary tasks in computer vision and video analytics …
ReViewNet: A fast and resource optimized network for enabling safe autonomous driving in hazy weather conditions
Adverse weather conditions such as fog, haze, snow, mist and glare create visibility
problems for applications of autonomous vehicles. To ensure safe and smooth operations in …
problems for applications of autonomous vehicles. To ensure safe and smooth operations in …
3DCD: Scene independent end-to-end spatiotemporal feature learning framework for change detection in unseen videos
Change detection is an elementary task in computer vision and video processing
applications. Recently, a number of supervised methods based on convolutional neural …
applications. Recently, a number of supervised methods based on convolutional neural …
Mor-uav: A benchmark dataset and baselines for moving object recognition in uav videos
M Mandal, LK Kumar, SK Vipparthi - Proceedings of the 28th ACM …, 2020 - dl.acm.org
Visual data collected from Unmanned Aerial Vehicles (UAVs) has opened a new frontier of
computer vision that requires automated analysis of aerial images/videos. However, the …
computer vision that requires automated analysis of aerial images/videos. However, the …
Scene independency matters: An empirical study of scene dependent and scene independent evaluation for CNN-based change detection
M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Visual change detection in video is one of the essential tasks in computer vision
applications. Recently, a number of supervised deep learning methods have achieved top …
applications. Recently, a number of supervised deep learning methods have achieved top …
Hidegan: A hyperspectral-guided image dehazing gan
Haze removal in images captured from a diverse set of scenarios is a very challenging
problem. The existing dehazing methods either reconstruct the transmission map or directly …
problem. The existing dehazing methods either reconstruct the transmission map or directly …
A robust medical image retrieval system based on wavelet optimization and adaptive block truncation coding
This paper presents a proposed method for medical image retrieval in order to search in a
database for an image that is similar to a query image. The proposed Medical Image …
database for an image that is similar to a query image. The proposed Medical Image …
MotionRec: A unified deep framework for moving object recognition
In this paper we present a novel deep learning framework to perform online moving object
recognition (MOR) in streaming videos. The existing methods for moving object detection …
recognition (MOR) in streaming videos. The existing methods for moving object detection …
3DFR: A swift 3D feature reductionist framework for scene independent change detection
In this paper we propose an end-to-end swift 3D feature reductionist framework (3DFR) for
scene independent change detection. The 3DFR framework consists of three feature …
scene independent change detection. The 3DFR framework consists of three feature …
Isdnet: Ai-enabled instance segmentation of aerial scenes for smart cities
Aerial scenes captured by UAVs have immense potential in IoT applications related to urban
surveillance, road and building segmentation, land cover classification, and so on, which are …
surveillance, road and building segmentation, land cover classification, and so on, which are …