Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
Visual SLAM and structure from motion in dynamic environments: A survey
In the last few decades, Structure from Motion (SfM) and visual Simultaneous Localization
and Map** (visual SLAM) techniques have gained significant interest from both the …
and Map** (visual SLAM) techniques have gained significant interest from both the …
Fully convolutional networks for semantic segmentation of very high resolution remotely sensed images combined with DSM
Recently, approaches based on fully convolutional networks (FCN) have achieved state-of-
the-art performance in the semantic segmentation of very high resolution (VHR) remotely …
the-art performance in the semantic segmentation of very high resolution (VHR) remotely …
Unified image and video saliency modeling
Visual saliency modeling for images and videos is treated as two independent tasks in
recent computer vision literature. While image saliency modeling is a well-studied problem …
recent computer vision literature. While image saliency modeling is a well-studied problem …
Video object segmentation and tracking: A survey
Object segmentation and object tracking are fundamental research areas in the computer
vision community. These two topics are difficult to handle some common challenges, such …
vision community. These two topics are difficult to handle some common challenges, such …
Recurrent fully convolutional neural networks for multi-slice MRI cardiac segmentation
In cardiac magnetic resonance imaging, fully-automatic segmentation of the heart enables
precise structural and functional measurements to be taken, eg from short-axis MR images …
precise structural and functional measurements to be taken, eg from short-axis MR images …
Deep learning based 3D segmentation: A survey
3D segmentation is a fundamental and challenging problem in computer vision with
applications in autonomous driving and robotics. It has received significant attention from the …
applications in autonomous driving and robotics. It has received significant attention from the …
Deep learning robotic guidance for autonomous vascular access
Medical robots have demonstrated the ability to manipulate percutaneous instruments into
soft tissue anatomy while working beyond the limits of human perception and dexterity …
soft tissue anatomy while working beyond the limits of human perception and dexterity …
Change detection in hyperspectral images using recurrent 3D fully convolutional networks
Hyperspectral change detection (CD) can be effectively performed using deep-learning
networks. Although these approaches require qualified training samples, it is difficult to …
networks. Although these approaches require qualified training samples, it is difficult to …