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Blsnet: a tri-branch lightweight network for gesture segmentation against cluttered backgrounds
Hand gesture segmentation is an essential step to recognize hand gestures for human–robot interaction. However, complex backgrounds and the variety...
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Background
The key aspects of intelligent vehicle systems are increased performance and safety in complex road traffic scenarios, which are achieved through the...
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Predictive control of aerial swarms in cluttered environments
Classical models of aerial swarms often describe global coordinated motion as the combination of local interactions that happen at the individual...
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Suction-based Grasp Point Estimation in Cluttered Environment for Robotic Manipulator Using Deep Learning-based Affordance Map
Perception and manipulation tasks for robotic manipulators involving highly-cluttered objects have become increasingly in-demand for achieving a more...
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Dynamic Capture Algorithm Based on Visual Background Extractor (Vibe)
Computer vision and motion capture have gradually developed, and the detection of moving objects has always been very important. Vibe is a simple and...
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Technical Background
This chapter provides the technical background of the collaborative fleet maneuvering problem. The basic knowledge of vehicle model and fleet...
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Crowd Counting via De-background Multicolumn Dynamic Convolutional Neural Network
The current state-of-the-art density map-based crowd counting methods have focused on designing convolution neural network (CNN)-based models to...
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Ship Detection from Highly Cluttered Images Using Convolutional Neural Network
Classification and Detection of vessels from cluttered images is an actively researched field of computer vision. The complexity of the coastal area...
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Using Deep Learning to Find Victims in Unknown Cluttered Urban Search and Rescue Environments
Purpose of ReviewWe investigate the first use of deep networks for victim identification in Urban Search and Rescue (USAR). Moreover, we provide the...
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Image Preprocessing-based Generalization and Transfer of Learning for Gras** in Cluttered Environments
In a cluttered environment in which objects are lying very closely to each other, the arranging motion is required before the robot attempts to grasp...
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Comparative Analysis of Deep Neural Networks for the Detection and Decoding of Data Matrix Landmarks in Cluttered Indoor Environments
Data Matrix patterns imprinted as passive visual landmarks have shown to be a valid solution for the self-localization of Automated Guided Vehicles...
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Feature-Aided SMC-PHD Filter for Nonlinear Multi-target Tracking in Cluttered Environments
The Sequential Monte Carlo Probability Hypothesis Density (SMC-PHD) filter is a permissive multi-target tracker, performing state estimation through...
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Online visual tracking via background-aware Siamese networks
With the rapid development of Siamese network based trackers, a set of related methods have produced considerable performance improvement. However,...
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CTA-FPN: Channel-Target Attention Feature Pyramid Network for Prohibited Object Detection in X-ray Images
Fast and accurate prohibited object detection in X-ray images is great challenging. Based on YOLOv6 object detection framework, in this paper,...
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Word Spotting in Cluttered Environment
In this paper, we present a novelSrivastava, Divya problem of handwrittenHarit, Gaurav word spotting in cluttered environment where a word is...
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Novel Image Processing Technique Using Thresholding and Deep Learning Model to Identify Plant Diseases in Complex Background
Every year tomato crops suffer huge losses due to the occurrence of disease outbreaks. Therefore, the identification of diseases has its importance...
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A Hybrid Face Recognition Scheme in a Heterogenous and Cluttered Environment
The recognition of human faces is an old application which can detect, track, and identify or verify human faces from a still or motioned picture...
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Formation control of unmanned rotorcraft systems with state constraints and inter-agent collision avoidance
We present in this paper a novel framework and distributed control laws for the formation of multiple unmanned rotorcraft systems, be it single-rotor...
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Grasp Configuration Synthesis from 3D Point Clouds with Attention Mechanism
Grasp generation is a crucial task in robotics, especially in unstructured environments, where robots must identify suitable grasp locations on...
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MGBM-YOLO: a Faster Light-Weight Object Detection Model for Robotic Gras** of Bolster Spring Based on Image-Based Visual Servoing
The rapid detection and accurate positioning of bolster spring with complex geometric features in cluttered background is highly important for the...