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Aerial Lifting: Neural Urban Semantic and Building Instance Lifting from Aerial Imagery

Aerial Lifting: Neural Urban Semantic and Building Instance ...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yuqi Zhang Guanying Chen Jiaxing Chen Shuguang Cui FNii CUHKSZ SSE CUHKSZ Sun Yat-sen University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

We present a neural radiance field method for urban-scale semantic and building-level instance segmentation from aerial images by lifting noisy 2D labels to 3D. This is a challenging problem due to two primary reasons. Firstly, objects in urban aerial images exhibit substantial variations in size, including buildings, cars, and roads, which pose a significant challenge for accurate 2D segmentation. Secondly, the 2D labels generated by existing segmentation methods suffer from the multi-view inconsistency problem, especially in the case of aerial images, where each image captures only a small portion of the entire scene. To overcome these limitations, we first introduce a scale-adaptive semantic label fusion strategy that enhances the segmentation of objects of varying sizes by combining labels predicted from different altitudes, harnessing the novel-view synthesis capabilities of NeRF. We then introduce a novel cross-view instance label grouping based on the 3D scene representation to mitigate the multi-view inconsistency problem in the 2D instance labels. Furthermore, we exploit multi-view reconstructed depth priors to improve the geometric quality of the reconstructed radiance field, resulting in enhanced segmentation results. Experiments on multiple real-world urban-scale datasets demonstrate that our approach outperforms existing methods, high-lighting its effectiveness. The source code is available at https://***/zyqz97/Aerial_lifting.

关键词： Instance segmentation Three-dimensional displays Accuracy source coding Semantic segmentation Semantics Buildings

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GraMDTA: Multimodal Graph Neural Networks for Predicting Drug-Target Associations

GraMDTA: Multimodal Graph Neural Networks for Predicting Dru...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jaswanth K. Yella Sudhir K. Ghandikota Anil G. Jegga Department of Electrical Engineering and Computer Science University of Cincinnati OH USA Division of Biomedical Informatics OH USA Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center OH USA Department of Pediatrics University of Cincinnati OH USA

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Identifying novel drug-target associations is vital for drug discovery. However, the screening of millions of small molecules for a selected target protein is challenging. Several computational approaches have been developed in the past using machine learning methods for computational drug-target association (DTA) prediction, which predominantly uses the structural data of drugs and proteins. Some of these approaches use knowledge graph networks and link prediction. To the best of our knowledge, there have been no approaches that use both structural learning, which offers molecular-based representations, and knowledge graph-based learning, which offers interaction-based representations, for DTA discovery. Based on the premise that multimodal sources of information acting complimentarily could improve the robustness of DTA predictions, we developed GraMDTA, a multimodal graph neural network that learns both structural and knowledge graph representations by utilizing multihead attention to fuse multimodal representations. We compared GraMDTA with other computational approaches for DTA prediction to demonstrate the power of multimodal fusion in the discovery of DTA.

关键词： Proteins Drugs Knowledge engineering Protein engineering source coding Benchmark testing Sampling methods

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On a spectral scaling technique for pitch control in the high-quality text-to-speech type system

On a spectral scaling technique for pitch control in the hig...

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： JuimgGpie Cjimg MyungJin Bae Dept. of Telecommun. Eng. Soongsil Univ. Seoul South Korea Dpt. of Telecommunication Engr Soongsil University Seoul South Korea

ISBN: (纸本)0780336941

Speech synthesis technique is classified into three groups; waveform coding, source coding and hybrid coding. Waveform coding and hybrid coding are used for sentence-based-synthesis by synthesis-by-analysis method; the difficulty of pitch altering makes them inappropriate for synthesis-by-rule. However, if it is possible to alter the pitch period when the waveform coding is used, synthesis-by-rule is available maintaining good intelligibility and naturalness comparable to the original speech. In this paper, we propose a new pitch alteration method that can change the pitch period in waveform coding by scaling the time-axis and where phase compensation is performed by using the zero-inserting and pitch-halving method.

关键词： Speech synthesis Speech coding Frequency domain analysis Time frequency analysis Cepstrum Telecommunication control source coding Very large scale integration Packaging Linear predictive coding

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MAP decoding of variable length code with substitution, insertion and deletion

MAP decoding of variable length code with substitution, inse...

引用

IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Zhe Wang Xiaolin Wu Department of Electrical and Computer Engineering McMaster University Hamilton ONT Canada Department of Computer and Information Science Polytechnic University Brooklyn NY USA

We propose a soft decision decoding algorithm for a variable-length encoded Markov source transmitted via a noisy channel that has all three types of errors - substitution, deletion, and insertion. The decoder aims to find a sequence, X, that maximizes the posterior probability, given a received sequence, Y. First, we assume the channel is a binary symmetric channel (BSC), and the input of the channel is a first order Markov source. We convert the MAP (maximum a posteriori) problem to one of finding a single-source longest path in a directed acyclic graph, which can be solved by dynamic programming. We also present a generalization of the BSC to include both insertion and deletion errors, and the development of a soft decision MAP decoding algorithm for this more challenging case, which is our main contribution.

关键词： Decoding Dynamic programming Algorithm design and analysis Computer errors Graphics Modems source coding Channel coding Constraint optimization Probability

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List sequence MAP decoding

List sequence MAP decoding

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IEEE Conference and Exhibition on Global Telecommunications (GLOBECOM)

作者： C.F. Leanderson C.-E.W. Sundberg Department of Electroscience Lund University Lund Sweden SundComm Chatham NJ USA

A list sequence (LS) maximum a posteriori probability (MAP) decoding algorithm for convolutional codes, that takes into account bitwise a priori probabilities and produces a rank ordered list of /spl Lscr/ sequence MAP estimates, can be obtained by modification of the metric increments of the serial list Viterbi algorithm. In this paper, we study the performance of LS-MAP decoding with genie-assisted error detection on the additive white Gaussian noise channel. Computer simulations and approximate analytical expressions, based on geometrical considerations are presented. We focus on the frame error rate and it is concluded that LS-MAP decoding with /spl Lscr/ > 1 often exploits a priori information more efficiently than conventional single sequence MAP decoding (/spl Lscr/ = 1). This leads in many cases to larger relative gains with LS-MAP than LS-ML decoding as /spl Lscr/ increases.

关键词： Decoding Viterbi algorithm Concatenated codes Convolutional codes Modulation coding source coding Cyclic redundancy check AWGN channels Performance analysis Delay

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TAFNet: A Three-Stream Adaptive Fusion Network for RGB-T Crowd Counting

TAFNet: A Three-Stream Adaptive Fusion Network for RGB-T Cro...

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IEEE International Symposium on Circuits and Systems

作者： Haihan Tang Yi Wang Lap-Pui Chau Schoo of Eecric nd Eecronic Engineering Nnyng Technoogic Universiy SingoreSchoo of Eecric nd Eecronic Engineering Nnyng Technoogic Universiy SingoreSchoo of Eecric nd Eecronic Engineering Nnyng Technoogic Universiy Singore

ISBN: (数字)9781665484855

ISBN: (纸本)9781665484862

In this paper, we propose a three-stream adaptive fusion network named TAFNet, which uses paired RGB and thermal images for crowd counting. Specifically, TAFNet is divided into one main stream and two auxiliary streams. We combine a pair of RGB and thermal images to constitute the input of main stream. Two auxiliary streams respectively exploit RGB image and thermal image to extract modality-specific features. Besides, we propose an Information Improvement Module (IIM) to fuse the modality-specific features into the main stream adaptively. Experiment results on RGBT-CC dataset show that our method achieves more than 20% improvement on mean average error and root mean squared error compared with state-of-the-art method. The source code will be publicly available at .

关键词： Adaptive systems Fuses Circuits and systems source coding Lighting Streaming media Feature extraction

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APACE: Agile and Perception-aware Trajectory Generation for Quadrotor Flights

APACE: Agile and Perception-aware Trajectory Generation for ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Xinyi Chen Yichen Zhang Boyu Zhou Shaojie Shen Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China School of Artificial Intelligence Sun Yat-Sen University Zhuhai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Various perception-aware planning approaches have attempted to enhance the state estimation accuracy during maneuvers, while the feature matchability among frames, a crucial factor influencing estimation accuracy, has often been overlooked. In this paper, we present APACE, an Agile and Perception-Aware trajeCtory gEneration framework for quadrotors aggressive flight, that takes into account feature matchability during trajectory planning. We seek to generate a perception-aware trajectory that reduces the error of visual-based estimator while satisfying the constraints on smoothness, safety, agility and the quadrotor dynamics. The perception objective is achieved by maximizing the number of covisible features while ensuring small enough parallax angles. Additionally, we propose a differentiable and accurate visibility model that allows decomposition of the trajectory planning problem for efficient optimization resolution. Through validations conducted in both a photorealistic simulator and real-world experiments, we demonstrate that the trajectories generated by our method significantly improve state estimation accuracy, with root mean square error (RMSE) reduced by up to an order of magnitude. The source code will be released to benefit the community 1 .

关键词： Accuracy Trajectory planning source coding Trajectory Safety Planning State estimation

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Speech coding method using fuzzy vector quantization

Speech coding method using fuzzy vector quantization

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Y. Asakawa A. Ichikawa S. Yajima K. Yamasaki Central Research Laboratory Hitachi and Limited Kokubunji Tokyo Japan Hitachi and Limited Yokohama Japan

A medium-based, high-quality speech coding method that is promising for producing high-quality speech is proposed. One of its main features is the application of a PSE (power-spectrum envelope) analysis method. Another feature is the application of fuzzy vector quantization (FVQ), which can reduce quantization distortion to below that of conventional VQ. Reduced FVQ (R-FVQ), which uses a k-nearest-neighbor technique, a code-word selection technique, and a predetermined table, is proposed for reducing both the bit rate and quantization distortion. Using R-FVQ, speech was coded at 8-kb/s and the synthetic speech was of high quality and sounded natural.< >

关键词： Speech coding Vector quantization Bit rate Speech analysis Speech synthesis source coding Poles and zeros Frequency domain analysis Frequency estimation Laboratories

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Layered BubbleTea Software Architecture Visualisation

Layered BubbleTea Software Architecture Visualisation

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IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT)

作者： Satrio Adi Rukmono Michel R. V. Chaudron Christopher Jeffrey Eindhoven University of Technology Eindhoven The Netherlands Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798331528485

ISBN: (纸本)9798331528492

This paper presents the Layered BubbleTea Visualisation, a novel approach to software visualisation that enhances the comprehension of software systems from an architectural perspective. The visualisation addresses the challenge of understanding complex software structures by mapping software components to architectural layers and elucidating their contents according to their relation to the stereotypical functionality of architectural layers. The paper details the development and presentation of the Layered BubbleTea Visualisation technique, illustrated using the source code of an Android email client application, K-9 Mail. We highlight the technique's potential to identify design issues and guide refactoring efforts. This work contributes to the field of software visualisation by offering a new approach to understanding and managing the complexity of software systems. Video URL-https://***/wvQNhmbyLtk

关键词： Visualization Software architecture source coding Layout Software systems Software Complexity theory Postal services

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Application of LCDP and Technology in Existing Business Systems in Enterprise

Application of LCDP and Technology in Existing Business Syst...

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Communication, Image and Signal Processing (CCISP), International Conference on

作者： Liqin Fu Feng Qiao Qin Lin Hanling Yang An Liu Xian Liu Hong Li Development Department China Mobile (Chengdu) Industrial Research Institute Chengdu China

ISBN: (数字)9798350356656

ISBN: (纸本)9798350356663

In the field of software development, Low-code Development Platform(LCDP) and low-code technology can automatically generate source code of business module, improving the efficiency of software development. However, for enterprises, there is a difficulty in applying LCDP and technology in existing business systems: the source code generated by LCDP cannot be integrated into other systems (such as existing systems) directly due to incompatible technology stacks. In an effort to mitigate the problem, these innovations are proposed in this paper: 1) A method to apply LCDP and technology in existing software system: extracting the visual code generation ability from LCDP as independent module for the purpose of reuse in existing business systems; 2) Designing an innovative architecture and method decoupled through technologies such as “Front-end and Back-end Separation”, “Micro Front-end” and “Micro-Service” so that code generation ability in the previous step and the code generated by it can be directly, easily and quickly integrated into existing business systems. Applying the method, the architecture and related technologies in this paper in existing business systems enables systems not only repeatedly generate code but also integrate the generated code, thereby enhancing development efficiency in enterprise. Currently, the methods and technologies outlined in this paper have been applied in enterprises, not only demonstrating the feasibility of this low-code code generation ability, the architecture with technologies especially emerging micro front-end and method to integrate, but also concluding that enterprise development efficiency is improved, and the more existing systems to apply in and the more modules are generated and integrated into, the greater the efficiency gains.

关键词： Visualization Technological innovation Codes source coding Computer architecture Signal processing Software systems Business Software development management

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