This paper addresses the critical issue of psychological safety in the design and operation of autonomous vehicles, which are increasingly integrated with artificial intelligence technologies. While traditional safety...
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As computer vision and human-computer interaction technologies are getting mature, vision-based auxiliary text reading has become the mainstream method to optimize learning and reading experience. To overcome the draw...
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Brain-inspired navigation technologies combine environmental perception,spatial cognition,and target navigation to create a comprehensive navigation research *** have used various sensors to gather environmental data ...
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Brain-inspired navigation technologies combine environmental perception,spatial cognition,and target navigation to create a comprehensive navigation research *** have used various sensors to gather environmental data and enhance environmental perception using multimodal information *** spatial cognition,a neural network model is used to simulate the navigation mechanism of the animal brain and to construct an environmental cognition ***,existing models face challenges in achieving high navigation success rate and *** addition,the limited incorporation of navigation mechanisms borrowed from animal brains necessitates further *** the basis of the braininspired navigation process,this paper launched a systematic study on brain-inspired environment perception,brain-inspired spatial cognition,and goal-based navigation in brain-inspired navigation,which provides a new classification of brain-inspired cognition and navigation techniques and a theoretical basis for subsequent experimental *** the future,brain-inspired navigation technology should learn from more perfect brain-inspired mechanisms to improve its generalization ability and be simultaneously applied to large-scale distributed intelligent body cluster *** multidisciplinary nature of braininspired navigation technology presents challenges,and multidisciplinary scholars must cooperate to promote the development of this technology.
With the rapid increase in wildfires in the past decade, it has become necessary to detect and predict these disasters to mitigate losses to ecosystems and human lives. In this paper, we present a novel solution - Hyp...
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ISBN:
(数字)9798331510954
ISBN:
(纸本)9798331510961
With the rapid increase in wildfires in the past decade, it has become necessary to detect and predict these disasters to mitigate losses to ecosystems and human lives. In this paper, we present a novel solution - Hyper-Drive3D - consisting of snapshot hyperspectral imaging and LiDAR, mounted on an Unmanned Ground Vehicle (UGV) that identifies areas inside forests at risk of becoming fuel for a forest fire. This system enables more accurate classification by analyzing the spectral signatures of forest vegetation. We conducted field trials in a controlled environment simulating forest conditions, yielding valuable insights into the system's effectiveness. Extensive data collection was also performed in a dense forest across varying environmental conditions and topographies to enhance the system's predictive capabilities for fire hazards and support a risk-informed, proactive forest management strategy. Additionally, we propose a framework for extracting moisture data from hyperspectral imagery and projecting it into 3D space.
Atmospheric haze degrades remote sensing images by obscuring critical details, diminishing data interpretation accuracy. This paper presents CLEAR-Net: Cascaded Local and External Attention Resource Network, a novel d...
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作者:
Liu, HaozheZhang, WentianLiu, FengWu, HaoqianShen, LinlinThe Computer Vision Institute
College of Computer Science and Software Engineering SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society The National Engineering Laboratory for Big Data System Computing Technology The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China
The vulnerability of automated fingerprint recognition systems (AFRSs) to presentation attacks (PAs) promotes the vigorous development of PA detection (PAD) technology. However, PAD methods have been limited by inform...
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Human facial action units (AUs) are mutually related in a hierarchical manner, as not only they are associated with each other in both spatial and temporal domains but also AUs located in the same/close facial regions...
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ISBN:
(数字)9798350353006
ISBN:
(纸本)9798350353013
Human facial action units (AUs) are mutually related in a hierarchical manner, as not only they are associated with each other in both spatial and temporal domains but also AUs located in the same/close facial regions show stronger relationships than those of different facial regions. While none of existing approach thoroughly model such hi-erarchical inter-dependencies among AUs, this paper proposes to comprehensively model multi-scale AU-related dynamic and hierarchical spatiotemporal relationship among AUs for their occurrences recognition. Specifically, we first propose a novel multi-scale temporal differencing network with an adaptive weighting block to explicitly capture facial dynamics across frames at different spatial scales, which specifically considers the heterogeneity of range and mag-nitude in different AUs' activation. Then, a two-stage strategy is introduced to hierarchically model the relationship among AUs based on their spatial distribution (i.e., local and cross-region AU relationship modelling). Experimental results achieved on BP4D and DISFA show that our approach is the new state-of-the-art in the field of AU occurrence recognition. Our code is publicly available at https://***/CVI-SZU/MDHR.
As an expanding field that caters to the needs of the elderly and people with disabilities, intelligent wheelchairs aim to enhance the efficiency and safety of individuals with disabilities. Path planning, a pivotal t...
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ISBN:
(数字)9798350379228
ISBN:
(纸本)9798350390780
As an expanding field that caters to the needs of the elderly and people with disabilities, intelligent wheelchairs aim to enhance the efficiency and safety of individuals with disabilities. Path planning, a pivotal technology under intelligent wheelchair systems, has emerged as a focal point of scholarly exploration. This paper proposes advancements in the vector field histogram plus (VFH+) algorithm, thereby introducing the adaptive VFH+ algorithm (AVFH+). Notably, this paper redefines the calculation of obstacle density and introduces the concept of custom target point density. By dynamically modulating the threshold, we effectively resolve the problems of oscillatory paths during obstacle avoidance, thus averting the predicament of the robot. In addition, the robot's speed is adaptively adjusted based on the opening width, and the trajectory is smoothed using Bezier path planning, enabling the robot to reach the target position through a shorter collision-free and smooth path. The improved AVFH+ algorithm demonstrates excellent path planning capability through multiple simulation experiments in various map environments with different starting points and target locations. The algorithm has the ability to adapt to complex environments, accurately perceive and avoid obstacles, and exhibits significant generalization capabilities. This makes it significant in dense area path planning, providing safer and more efficient mobility solutions in areas such as smart wheelchairs, and actively contributing to the quality of life of people with disabilities. Future research could explore the consideration of dynamic obstacles and validate the performance of the algorithm in real-world environments.
Tactile sensing is significant for robotics since it can obtain physical contact information during manipulation. To capture multimodal contact information within a compact framework, we designed a novel sensor called...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
Tactile sensing is significant for robotics since it can obtain physical contact information during manipulation. To capture multimodal contact information within a compact framework, we designed a novel sensor called ViTacTip, which seamlessly integrates both tactile and visual perception capabilities into a single, integrated sensor unit. ViTacTip features a transparent skin to capture fine features of objects during contact, which can be known as the see-through-skin mechanism. In the meantime, the biomimetic tips embedded in ViTacTip can amplify touch motions during tactile perception. For comparative analysis, we also fabricated a ViTac sensor devoid of biomimetic tips, as well as a TacTip sensor with opaque skin. Furthermore, we develop a Generative Adversarial Network (GAN)-based approach for modality switching between different perception modes, effectively alternating the emphasis between vision and tactile perception modes. We conducted a performance evaluation of the proposed sensor across three distinct tasks: i) grating identification, ii) pose regression, iii) contact localization and force estimation. In the grating identification task, ViTacTip demonstrated an accuracy of 99.72%, surpassing TacTip, which achieved 94.60%. It also exhibited superior performance in both pose and force estimation tasks with the minimum error of 0.08 mm and 0.03N, respectively, in contrast to ViTac’s 0.12 mm and 0.15N. Results indicate that ViTacTip outperforms single-modality sensors.
Tactile pose estimation and tactile servoing are fundamental capabilities of robot touch. Reliable and precise pose estimation can be provided by applying deep learning models to high-resolution optical tactile sensor...
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