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Closed-loop active object recognition with constrained illumination power

Closed-loop active object recognition with constrained illum...

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conference on Real-Time image processing and Deep Learning

作者： Noom, Jacques Soloviev, Oleg Smith, Carlas Verhaegen, Michel Delft Univ Technol Delft Ctr Syst & Control Mekelweg 2 NL-2628 CD Delft Netherlands Flexible Opt BV Polakweg 10-11 NL-2288 GG Rijswijk Netherlands

ISBN: (纸本)9781510650817;9781510650800

Some applications require high level of image-based classification certainty while keeping the total illumination energy as low as possible. Examples are minimally invasive visual inspection in Industry 4.0, and medical imaging systems such as computed tomography, in which the radiation dose should be kept "as low as is reasonably achievable". We introduce a sequential object recognition scheme aimed at minimizing phototoxicity or bleaching while achieving a predefined level of decision accuracy. The novel online procedure relies on approximate weighted Bhattacharyya coefficients for determination of future inputs. Simulation results on the MNIST handwritten digit database show how the total illumination energy is decreased with respect to a detection scheme using constant illumination.

关键词： Active fault diagnosis Auxiliary signal design Machine Vision Computational Tomography Medical imaging Industry 4.0

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Multiphoton microscopy in cosmetic research - a mini review on recent advancements

Multiphoton microscopy in cosmetic research - a mini review ...

引用

conference on Photonics in Dermatology and Plastic Surgery

作者： Wang, Yucong (Connie) Li, Shuting Wang, Hequn (Tracy) LOreal China Res & Innovat 550 Jinyu Rd Shanghai Peoples R China

ISBN: (数字)9781510647404

ISBN: (纸本)9781510647404;9781510647398

Multiphoton microscopy (MPM) has been discovered for several decades now. With non-invasive nature, subcellular resolution, relatively high imaging depth, distinctive biochemical-based imaging contrast, and the ability to be combined with other imaging and spectroscopic modes, MPM has been applied in many different fields in characterizing biological tissues and organisms, including medical diagnosis and treatment, drug development and penetration, cosmetic research, etc. In particular, its application in cosmetic industry has been advancing exponentially. This review will be focusing on a brief historical review and some recent advancements of MPM with a focus on its applications in cosmetic research. With the developments in both the hardware and software, such as the recent improvements in tunable laser sources, scanning speed and angles, the speed of computing, real-time image processing, etc., MPM will continue to grow dramatically. Together with other imaging and spectroscopic modalities, it is envisioned that higher imaging resolution, larger image field, faster image acquisition and processing, as well as more complementary information will be achieved, and will help revolutionize the field of cosmetic research.

关键词： Skin 3D image processing Microscopy 3D modeling Luminescence Second-harmonic generation Collagen Multiphoton microscopy signal detection Zinc oxide

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Cross-modal Collaboration for Augmented Few-Shot image Classification

Cross-modal Collaboration for Augmented Few-Shot Image Class...

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IEEE International conference on Information Communication and signal processing (ICICSP)

作者： Chunxiang He Kaiyuan Feng Hongyu Zhao School of Electronic Engineering Xidian University Xi'an China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Training high-performance image classification models typically requires a large amount of labeled data. However, in practical applications, obtaining sufficient and high-quality training data is often challenging due to high data collection costs and annotation difficulties. To address this, we propose the Text and image Collaboration-based Augmented Few-Shot Learning method (TICA-FSL). TICA-FSL leverages auxiliary modality data to generate diverse sample features through collaborative augmentation. By incorporating text features into the visual embedding space, it enhances the performance and robustness of classification models under data-scarce conditions. Experiments on CUB-200 and Oxford-102 datasets show that TICA-FSL significantly outperforms baseline methods with accuracy improvements of 4%and 2%respectively in 5-shot and 1-shot scenarios. The results demonstrate the effectiveness of utilizing multi-modal data from text and images for few-shot learning, expanding the capabilities of deep learning in practical applications.

关键词： Training Visualization Collaboration Training data signal processing Data collection Robustness Data models Few shot learning image classification

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Generalizable Real-time Accelerated Dynamic MRI

Generalizable Real-time Accelerated Dynamic MRI

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Silpa Babu Wahidul Alam Rushdi Zahid Rusho Sajan Goud Lingala Namrata Vaswani ECE Dept Iowa State University USA BME Dept University of Iowa USA

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

We introduce a real-time undersampled dynamic MRI algorithm, termed FewShot-AltGDmin-MRI, that is generalizable: works for many different applications and sampling trajectories without any application-specific parameter tuning. FS-AGM-MRI operates in real-time after processing the first short mini-batch, i.e., it can provide a reconstruction of each new image frame as soon as the MRI scan data for that frame arrives. It also provides a second set of improved quality reconstructions after a short delay. We compare our algorithm against many state of the art batch MRI algorithms, including Deep Learning (DL) based ones, on 17 different retrospectively undersampled datasets and two prospective datasets. FS-AGM-MRI is the only approach that provides accurate recovery for all datasets while also being one of the fastest.

关键词： Magnetic resonance imaging Heuristic algorithms signal processing algorithms signal processing Real-time systems Trajectory Delays Speech processing image reconstruction Tuning

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Automatic target detection utilizing an Edge IR vision transformer (EIR-ViT) 33

Automatic target detection utilizing an Edge IR vision trans...

引用

conference on Automatic Target Recognition xxxIII

作者： Adams, Ethan R. Depoian, Arthur C., II Kurz, Aidan G. Bailey, Colleen P. Guturu, Parthasarathy Univ North Texas Dept Elect Engn Denton TX 76207 USA

ISBN: (纸本)9781510661561;9781510661578

The detection and recognition of targets within imagery and video analysis is vital for military and commercial applications. The development of infrared sensor devices for tactical aviation systems imagery has increased the performance of target detection. Due to the advancements of infrared sensors capabilities, their use for field operations such as visual operations (visops) or reconnaissance missions that take place in a variety of operational environments have become paramount. Many techniques implemented stretch back to 1970, but were limited due to computational power. The AI industry has recently been able to bridge the gap between traditional signal processing tools and machine learning. Current state of the art target detection and recognition algorithms are too bloated to be applied for on ground or aerial mission reconnaissance. Therefore, this paper proposes Edge IR Vision Transformer (EIR-ViT), a novel algorithm for automatic target detection utilizing infrared images that is lightweight and operates on the edge for easier deployability.

关键词： Automatic Target Detection Vision Transformer Infrared Imaging Object Detection FLIR image FLIR dataset Edge Computing

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Stochastic Vector Approximate Message Passing with applications to Phase Retrieval

Stochastic Vector Approximate Message Passing with Applicati...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Hajime Ueda Shun Katakami Masato Okada Graduate School of Frontier Sciences The University of Tokyo Kashiwa Chiba Japan

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Phase retrieval refers to the problem of recovering a high-dimensional vector ${\mathbf{x}} \in {\mathbb{C}^N}$ from the magnitude of its linear transform z = Ax, observed through a noisy channel. To improve the ill-posed nature of the inverse problem, it is a common practice to observe the magnitude of linear measurements z (1) = A (1) x,…, z (L) = A (L) x using multiple sensing matrices A (1) ,…, A (L) , with ptychographic imaging being a remarkable example of such strategies. Inspired by existing algorithms for ptychographic reconstruction, we introduce stochasticity to Vector Approximate Message Passing (VAMP), a computationally efficient algorithm applicable to a wide range of Bayesian inverse problems. By testing our approach in the setup of phase retrieval, we show the superior convergence speed of the proposed algorithm.

关键词： Inverse problems Message passing signal processing algorithms Imaging Approximation algorithms Vectors Bayes methods Probes image reconstruction Convergence

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FiTGAN: Content Fusion with Style Transformation for Few-shot image Generation

FiTGAN: Content Fusion with Style Transformation for Few-sho...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Yingbo Zhou Pengyu Zhang Yutong Ye Zhihao Yue xian Wei Mingsong Chen MoE Eng. Research Center of SW/HW Co-Design Tech. and App. East China Normal University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Due to the semantic entanglement in fusion strategies or unstable training in complicated image transformations, existing few-shot image generation methods still suffer from low generation quality and diversity. To tackle the above problems, we propose a novel fusion- and transformation-based framework named content Fusion with style Transformation Generative Adversarial Network (FiTGAN) for few-shot image generation. The basic assumption is that any image consists of a collection of content-related and style-related features. FiTGAN disentangles internal representations with two independent encoders and combines the fused contents and transformed styles to generate new images. Specifically, we design a multi-scale content fusion strategy and a reparameterized style transformation mechanism to learn more fine-grained semantics without changing category-relevant attributes. Furthermore, we formulate a content reconstruction loss and a style divergence loss to provide better training stability and generation performance. Comprehensive experiments on three well-known datasets demonstrate that FiTGAN can not only produce more realistic and diverse images for few-shot image generation but also achieve better classification accuracy for downstream visual applications with limited data.

关键词： Training Measurement Visualization image synthesis Semantics Transforms signal processing Stability analysis Speech processing image reconstruction

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SPT: Sequence Prompt Transformer for Interactive image Segmentation

SPT: Sequence Prompt Transformer for Interactive Image Segme...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Senlin Cheng Haopeng Sun Tao xie Hangyue Zhao Yiqiang Chen Bolei xu xiaoBo Li Ant Group Hangzhou China Beiiing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China BAIDU Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Interactive segmentation aims to extract objects of interest from an image based on user-provided clicks. In real-world applications, there is often a need to segment a series of images featuring the same target object. However, existing methods typically process one image at a time, failing to consider the sequential nature of the images. To overcome this limitation, we propose a novel method called Sequence Prompt Transformer (SPT), the first to utilize sequential image information for interactive segmentation. Our model comprises two key components: (1) Sequence Prompt Transformer (SPT) for acquiring information from sequence of images, clicks and masks to improve accurate. (2) Topk Prompt Selection (TPS) selects precise prompts for SPT to further enhance the segmentation effect. Additionally, we create the ADE20K-Seq benchmark to better evaluate model performance. We evaluate our approach on multiple benchmark datasets and show that our model surpasses state-of-the-art methods across all datasets.

关键词： image segmentation Accuracy Benchmark testing signal processing Transformers Acoustics Speech processing

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A dual-band millimeter-wave MIMO antenna based on SIW for 5G applications 7

A dual-band millimeter-wave MIMO antenna based on SIW for 5G...

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7th International conference on Communication, image and signal processing, CCISP 2022

作者： Zhang, Jie Du, Chengzhu Yang, Fuhui Peng, Huanchen College of Electronics and Information Engineering Shanghai University of Electric Power Shanghai China CETC Shanghai Microwave Communication Co Ltd Shanghai China

ISBN: (数字)9781665459594

ISBN: (纸本)9781665459594

A two-port dual-band millimeter-wave MIMO antenna based on SIW functioning in 5G is presented in this paper. Grounded coplanar waveguide GCPW is used for better impedance matching on antenna elements. This antenna is innovative in that it combines MIMO technology with SIW technology to improve isolation and communication quality. Moreover, double dumbbell-shaped slots are etched inside SIW resonator. Multi-modes are excited by this groove, which results in dual-frequency and broadband antenna performance. The antenna is printed on substrate Rogers 5880 with dimensions of 21.2x 19.2x 0.508 mm3. The proposed SIW antenna is capable of working with the 28GHz (25.74 GHz-29.79 GHz) and 38GHz (37.18GHz-41.8GHz) bands of 5G mmWaves. In addition, it demonstrates high isolation of more than-20 dB, good gain above 8dBi, FBR around 15dB and ECC less than 0.018 in the whole working band. It has good prospects in 5G applications. © 2022 IEEE.

关键词： Millimeter waves

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Siracusa: A Low-Power On-Sensor RISC-V SoC for Extended Reality Visual processing in 16nm CMOS 49

Siracusa: A Low-Power On-Sensor RISC-V SoC for Extended Real...

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IEEE 49th European Solid-State Circuits conference (ESSCIRC)

作者： Scherer, Moritz Eggimann, Manuel Di Mauro, Alfio Prasad, Arpan Suravi Conti, Francesco Rossi, Davide Gomez, Jorge Tomas Li, Ziyun Sarwar, Syed Shakib Wang, Zhao De Salvo, Barbara Benini, Luca Swiss Fed Inst Technol Dept Informat Technol & Elect Engn Zurich Switzerland Univ Bologna Dept Elect Elect & Informat Engn Bologna Italy Meta Real Labs Res Pittsburgh PA USA

ISBN: (纸本)9798350304206

Extended Reality (xR) has become increasingly popular in recent years, with applications in entertainment, education, healthcare, and more. However, mass adoption of xR technology still faces several challenges in meeting stringent latency and power consumption requirements. On-sensor computing, where a capable xR processor is tightly packaged with an image sensor, is a promising technology that can help address these challenges as it provides several benefits, including reduced data analysis latency, low power consumption, small form factor, and greater privacy. This work introduces Siracusa, an on-camera computing platform for next-generation xR devices. Siracusa features a flexible mixed-precision Machine Learning (ML) accelerator and a cluster of application-tuned RISC-V cores, sharing a highly configurable on-chip memory hierarchy designed to minimize expensive data copies. As a result, Siracusa achieves a peak energy efficiency of 9.9 TOp/J for deep neural network (DNN) inference, an increase of 1.2 x compared to similar designs, while supporting complex, heterogeneous application workloads, which combine ML with conventional signal processing and control.

关键词： System-on-chip

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