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Journal articles on the topic 'Encoder optimization'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

Hassan, Hammad, Muhammad Nasir Khan, Syed Omer Gilani, et al. "H.264 Encoder Parameter Optimization for Encoded Wireless Multimedia Transmissions." IEEE Access 6 (2018): 22046–53. http://dx.doi.org/10.1109/access.2018.2824835.

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Hamza, Ahmed M., Mohamed Abdelazim, Abdelrahman Abdelazim, and Djamel Ait-Boudaoud. "HEVC Rate-Distortion Optimization with Source Modeling." Electronic Imaging 2021, no. 10 (2021): 259–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.10.ipas-259.

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The Rate-Distortion adaptive mechanisms of MPEG-HEVC (High Efficiency Video Coding) and its derivatives are an incremental improvement in the software reference encoder, providing a selective Lagrangian parameter choice which varies by encoding mode (intra or inter) and picture reference level. Since this weighting factor (and the balanced cost functions it impacts) are crucial to the RD optimization process, affecting several encoder decisions and both coding efficiency and quality of the encoded stream, we investigate an improvement by modern reinforcement learning methods. We develop a neur

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Wang, Lei, Qimin Ren, Jingang Jiang, Hongxin Zhang, and Yongde Zhang. "Recent Patents on Magnetic Encoder and its use in Rotating Mechanism." Recent Patents on Engineering 13, no. 3 (2019): 194–200. http://dx.doi.org/10.2174/1872212112666180628145856.

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Background: The application of magnetic encoder relieves the problem of reliable application of servo system in vibration field. The magnetic encoder raises the efficiency and reliability of the system, and from structural considerations, the magnetic encoder is divided into two parts: signal conversion and structural support. Objective: In order to improve the accuracy of the magnetic encoder, its structure is constantly improving. To evaluate a magnetic encoder, the accuracy is a factor, meanwhile, the structure of magnetic encoder is one of the key factors that make difference in the accura

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M, Kishan, Kruthika B A, Mythreye S R, and Abhishek R Palanker. "Optimized 32-Bit Multirate Fully Parallel LDPC Encoder for Advanced Applications." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–7. https://doi.org/10.55041/ijsrem39486.

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Abstract—This paper presents a 32-bit multirate fully parallel Low-Density Parity-Check (LDPC) encoder tailored for advanced communication systems. The proposed design focuses on optimizing the architecture to achieve high throughput, low latency, and efficient resource utilization. By incorporating an enhanced parallel processing framework, the encoder supports multiple rates while maintaining robust error-correction capabilities. Its scalable structure and efficient implementation make it suitable for high-performance applications, including modern wireless communication standards. Simulatio

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P. Anjaneya and P. Sushma. "Efficient 4-Bit Encoder Design with Memristor Technology and SAPON Integration." International Research Journal on Advanced Engineering Hub (IRJAEH) 2, no. 09 (2024): 2296–302. http://dx.doi.org/10.47392/irjaeh.2024.0314.

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This study displays three different encoder setups: CMOS, Memristor, and Pseudo NMOS. Digital logic gate designs that use memristors provide an alternative to the present IC architecture. This computing architecture will be among the upcoming ones. The poly silicon gate of an NMOS transistor can be used to build memristors, making MRL gates simple to fabricate. The encoder's design makes use of four bits. When comparing the recommended 4-bit encoder with memristor logic to one with CMOS logic and pseudo-N MOS logic, the former requires less power. This paper also presents a 4-bit encoder desig

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Lee, Yoon Jin, Dong In Bae, and Gwang Hoon Park. "HEVC Encoder Optimization using Depth Information." Journal of Broadcast Engineering 19, no. 5 (2014): 640–55. http://dx.doi.org/10.5909/jbe.2014.19.5.640.

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7

Wang, Shanshe, Falei Luo, Siwei Ma, et al. "Low complexity encoder optimization for HEVC." Journal of Visual Communication and Image Representation 35 (February 2016): 120–31. http://dx.doi.org/10.1016/j.jvcir.2015.12.005.

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Merel, Josh, Donald M. Pianto, John P. Cunningham, and Liam Paninski. "Encoder-Decoder Optimization for Brain-Computer Interfaces." PLOS Computational Biology 11, no. 6 (2015): e1004288. http://dx.doi.org/10.1371/journal.pcbi.1004288.

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Hanli Wang, Ming-Yan Chan, S. Kwong, and Chi-Wah Kok. "Novel quantized DCT for video encoder optimization." IEEE Signal Processing Letters 13, no. 4 (2006): 205–8. http://dx.doi.org/10.1109/lsp.2005.863691.

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Bariani, M., P. Lambruschini, and M. Raggio. "An Efficient Multi-Core SIMD Implementation for H.264/AVC Encoder." VLSI Design 2012 (May 29, 2012): 1–14. http://dx.doi.org/10.1155/2012/413747.

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The optimization process of a H.264/AVC encoder on three different architectures is presented. The architectures are multi- and singlecore and SIMD instruction sets have different vector registers size. The need of code optimization is fundamental when addressing HD resolutions with real-time constraints. The encoder is subdivided in functional modules in order to better understand where the optimization is a key factor and to evaluate in details the performance improvement. Common issues in both partitioning a video encoder into parallel architectures and SIMD optimization are described, and

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Hou, Han, Guohua Cao, Hongchang Ding, and Kun Li. "Research on Particle Swarm Compensation Method for Subdivision Error Optimization of Photoelectric Encoder Based on Parallel Iteration." Sensors 22, no. 12 (2022): 4456. http://dx.doi.org/10.3390/s22124456.

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Photoelectric encoders are widely used in high-precision measurement fields such as industry and aerospace because of their high precision and reliability. In order to improve the subdivision accuracy of moiré grating signals, a particle swarm optimization compensation model for grating the subdivision error of a photoelectric encoder based on parallel iteration is proposed. In the paper, an adaptive subdivision method of a particle swarm search domain based on the honeycomb structure is proposed, and a raster signal subdivision error compensation model based on the multi-swarm particle swarm

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12

Karim, Ahmad M., Hilal Kaya, Mehmet Serdar Güzel, Mehmet R. Tolun, Fatih V. Çelebi, and Alok Mishra. "A Novel Framework Using Deep Auto-Encoders Based Linear Model for Data Classification." Sensors 20, no. 21 (2020): 6378. http://dx.doi.org/10.3390/s20216378.

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This paper proposes a novel data classification framework, combining sparse auto-encoders (SAEs) and a post-processing system consisting of a linear system model relying on Particle Swarm Optimization (PSO) algorithm. All the sensitive and high-level features are extracted by using the first auto-encoder which is wired to the second auto-encoder, followed by a Softmax function layer to classify the extracted features obtained from the second layer. The two auto-encoders and the Softmax classifier are stacked in order to be trained in a supervised approach using the well-known backpropagation a

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Yang, Xiaoshan, Baochen Xiong, Yi Huang, and Changsheng Xu. "Cross-Modal Federated Human Activity Recognition via Modality-Agnostic and Modality-Specific Representation Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (2022): 3063–71. http://dx.doi.org/10.1609/aaai.v36i3.20213.

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In this paper, we propose a new task of cross-modal federated human activity recognition (CMF-HAR), which is conducive to promote the large-scale use of the HAR model on more local devices. To address the new task, we propose a feature-disentangled activity recognition network (FDARN), which has five important modules of altruistic encoder, egocentric encoder, shared activity classifier, private activity classifier and modality discriminator. The altruistic encoder aims to collaboratively embed local instances on different clients into a modality-agnostic feature subspace. The egocentric encod

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Cho, Jung-Hyun, Myung-Soo Lee, Han-Soo Jeong, Chang-Suk Kim, and Dae-Jea Cho. "Optimization of H.264 Encoder based on Hardware Implementation in Embedded System." Journal of the Korea Academia-Industrial cooperation Society 11, no. 8 (2010): 3076–82. http://dx.doi.org/10.5762/kais.2010.11.8.3076.

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Cahani, Ilda, and Marcus Stiemer. "Mathematical optimization and machine learning to support PCB topology identification." Advances in Radio Science 21 (December 1, 2023): 25–35. http://dx.doi.org/10.5194/ars-21-25-2023.

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Abstract. In this paper, we study an identification problem for schematics with different concurring topologies. A framework is proposed, that is both supported by mathematical optimization and machine learning algorithms. Through the use of Python libraries, such as scikit-rf, which allows for the emulation of network analyzer measurements, and a physical microstrip line simulation on PCBs, data for training and testing the framework are provided. In addition to an individual treatment of the concurring topologies and subsequent comparison, a method is introduced to tackle the identification

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Wali, Ibtissem, Amina Kessentini, Mohamed Ali Ben Ayed, and Nouri Masmoudi. "DSP TMS320C6678 Based SHVC Encoder Implementation and its Optimization." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 5 (2022): 24–31. http://dx.doi.org/10.35940/ijrte.e6656.0110522.

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The programmable processors newest technologies, as for example the multicore Digital Signal Processors (DSP), offer a promising solution for overcoming the complexity of the real time video encoding application. In this paper, the SHVC video encoder was effectively implemented just on a single core among the eight cores of TMS320C6678 DSP for a Common Intermediate Format (CIF)input video sequence resolution(352x288). Performance optimization of the SHVC encoder had reached up 41% compared to its reference software enabling a real-time implementation of the SHVC encoder for CIF input videos se

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Ibtissem, Wali, Kessentini Amina, Ali Ben Ayed Mohamed, and Masmoudi Nouri. "DSP TMS320C6678 Based SHVC Encoder Implementation and its Optimization." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 5 (2022): 24–31. https://doi.org/10.35940/ijrte.E6656.0110522.

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The programmable processors newest technologies, as for example the multicore Digital Signal Processors (DSP), offer a promising solution for overcoming the complexity of the real time video encoding application. In this paper, the SHVC video encoder was effectively implemented just on a single core among the eight cores of TMS320C6678 DSP for a Common Intermediate Format (CIF)input video sequence resolution(352x288). Performance optimization of the SHVC encoder had reached up 41% compared to its reference software enabling a real-time implementation of the SHVC encoder for CIF input videos se

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18

Bitriá, Ricard, and Jordi Palacín. "Optimal PID Control of a Brushed DC Motor with an Embedded Low-Cost Magnetic Quadrature Encoder for Improved Step Overshoot and Undershoot Responses in a Mobile Robot Application." Sensors 22, no. 20 (2022): 7817. http://dx.doi.org/10.3390/s22207817.

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The development of a proportional–integral–derivative (PID) control system is a simple, practical, highly effective method used to control the angular rotational velocity of electric motors. This paper describes the optimization of the PID control of a brushed DC motor (BDCM) with an embedded low-cost magnetic quadrature encoder. This paper demonstrates empirically that the feedback provided by low-cost magnetic encoders produces some inaccuracies and control artifacts that are not usually considered in simulations, proposing a practical optimization approach in order to improve the step overs

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19

Li, Hui, Tianpeng Pan, and Lili Zhang. "Enhanced Remote Sensing Image Compression Method Using Large Network with Sparse Extracting Strategy." Electronics 13, no. 13 (2024): 2677. http://dx.doi.org/10.3390/electronics13132677.

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Deep neural networks based on hyper-encoders play a critical role in estimating prior distributions in remote sensing image compression issues. However, most of the existing encoding methods suffer from a problem on the hyper-encoding side, namely the mismatch of extraction ability with the encoder. This ability bias results in likelihood features that fail to extract sufficient information from latent representations. To solve this problem, the feature extraction capabilities of the hyper-encoder are enhanced to better estimate the Gaussian likelihood of the latent representation in end-to-en

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Gurauskis, Donatas, Krzysztof Przystupa, Artūras Kilikevičius, et al. "Performance Analysis of an Experimental Linear Encoder’s Reading Head under Different Mounting and Dynamic Conditions." Energies 15, no. 16 (2022): 6088. http://dx.doi.org/10.3390/en15166088.

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The performance of an optical linear encoder is described and evaluated by certain parameters such as its resolution, accuracy and repeatability. The best encoder for a particular application, just like other sensors, is usually selected according these parameters. There are, however, many side effects that have a direct influence on the optimal operation of an encoder. In order to understand how to minimize these harmful effects, a deeper knowledge of an encoder’s performance and a method for determining these factors are necessary. The main aspects of an encoder’s accuracy, resolution and re

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21

Scanlan, Anthony, Daniel O’Hare, Mark Halton, Vincent O’Brien, Brendan Mullane, and Eric Thompson. "Analysis of feedback predictive encoder based ADCs." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 36, no. 1 (2017): 129–52. http://dx.doi.org/10.1108/compel-12-2015-0464.

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Purpose The purpose of this paper is to present analysis of the feedback predictive encoder-based analog-to-digital converter (ADC). Design/methodology/approach The use of feedback predictive encoder-based ADCs presents an alternative to the traditional two-stage pipeline ADC by replacing the input estimate producing first stage of the pipeline with a predictive loop that also produces an estimate of the input signal. Findings The overload condition for feedback predictive encoder ADCs is dependent on input signal amplitude and frequency, system gain and filter order. The limitation on the pra

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22

Hung-Chi Fang, Yu-Wei Chang, Tu-Chih Wang, Chao-Tsung Huang, and Liang-Gee Chen. "High-performance JPEG 2000 encoder with rate-distortion optimization." IEEE Transactions on Multimedia 8, no. 4 (2006): 645–53. http://dx.doi.org/10.1109/tmm.2006.876305.

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23

Vudadha, Chetan, Srinivasan Rajagopalan, Aditya Dusi, P. Sai Phaneendra, and M. B. Srinivas. "Encoder-Based Optimization of CNFET-Based Ternary Logic Circuits." IEEE Transactions on Nanotechnology 17, no. 2 (2018): 299–310. http://dx.doi.org/10.1109/tnano.2018.2800015.

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24

Dumitrescu, Sorina. "Fast Encoder Optimization for Multi-Resolution Scalar Quantizer Design." IEEE Transactions on Information Theory 57, no. 3 (2011): 1520–29. http://dx.doi.org/10.1109/tit.2011.2104990.

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25

Li, Jun, and Wenyi Zhang. "Asymptotically Optimal Status Update Compression in Multi-Source System: Age–Distortion Tradeoff." Entropy 27, no. 7 (2025): 664. https://doi.org/10.3390/e27070664.

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We consider a compression problem in a multi-source status-updating system through a representative two-source scenario. The status updates are generated by two independent sources following heterogeneous Poisson processes. These updates are then compressed into binary strings and sent to the receiver via a shared, error-free channel with a unit rate. We propose two compression schemes—a multi-quantizer compression scheme, where a dedicated quantizer–encoder pair is assigned to each source for compression, and a single-quantizer compression scheme, employing a unified quantizer–encoder pair sh

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Chen, Baifan, Haowu Zhao, Ruyi Zhu, and Yemin Hu. "Marked-LIEO: Visual Marker-Aided LiDAR/IMU/Encoder Integrated Odometry." Sensors 22, no. 13 (2022): 4749. http://dx.doi.org/10.3390/s22134749.

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In this paper, we propose a visual marker-aided LiDAR/IMU/encoder integrated odometry, Marked-LIEO, to achieve pose estimation of mobile robots in an indoor long corridor environment. In the first stage, we design the pre-integration model of encoder and IMU respectively to realize the pose estimation combined with the pose estimation from the second stage providing prediction for the LiDAR odometry. In the second stage, we design low-frequency visual marker odometry, which is optimized jointly with LiDAR odometry to obtain the final pose estimation. In view of the wheel slipping and LiDAR deg

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Wang, Xiaoyi, Chengxiang Zhao, Longyuan Xiao, et al. "Self-Calibration Method for Circular Encoder Based on Two Reading Heads with Adjustable Positions." Machines 12, no. 4 (2024): 246. http://dx.doi.org/10.3390/machines12040246.

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To improve the measuring accuracy of circular encoders in special applications, self-calibration of the circular encoder is necessary. The commonly used self-calibration method, namely the Equal Division Average (EDA) method, requires a large number of reading heads and cannot be used when the structural space is limited. In this paper, a self-calibration method for a circular encoder based on two reading heads with adjustable positions (TRAP) is proposed. This TRAP method uses two reading heads to simulate multiple reading heads, which can be used to achieve self-calibration of circular encod

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Huang, Yatao, Zihan Su, Di Chang, Yunke Sun, and Jiubin Tan. "Error Analysis of an Economical On-Site Calibration System for Linear Optical Encoders." Metrology 4, no. 1 (2024): 131–40. http://dx.doi.org/10.3390/metrology4010009.

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A calibration system was designed to evaluate the accuracy of linear optical encoders at the micron level in a fast and economical manner. The system uses a commercial interferometer and motor stage as the calibrator and moving platform. Error analysis is necessary to prove the effectiveness and identify areas for optimization. A fixture was designed for the scale and interferometer target to meet the Abbe principle. A five-degree-of-freedom manual stage was utilized to adjust the reading head in optimal or suboptimal working conditions, such as working distance, offset, and angular misalignme

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Madiwa, Shweta M., and Vishwanath Burkpalli. "Sine Cosine Based Harris Hawks Optimizer: A Hybrid Optimization Algorithm for Skin Cancer Detection Using Deep Stack Auto Encoder." Revue d'Intelligence Artificielle 36, no. 5 (2022): 697–708. http://dx.doi.org/10.18280/ria.360506.

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Skin cancer is becoming major problems due to its tremendous growth. Skin cancer is a malignant skin lesion, which may cause damage to human. Hence, prior detection and precise medical diagnosis of the skin lesion is essential. In medical practice, detection of malignant lesions needs pathological examination and biopsy, which is expensive. The existing techniques need a brief physical inspection, which is imprecise and time-consuming. This paper presents a computer-assisted skin cancer detection strategy for detecting the skin lesion in skin images using deep stacked auto encoder. Sine Cosine

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Whit Ney, Heh, Ab Al-Hadi Ab Rahman, Ainy Haziyah Awab, Mohd Shahrizal Rusli, Usman Ullah Sheikh, and Goh Kam Meng. "Hardware design of a scalable and fast 2-D hadamard transform for HEVC video encoder." Indonesian Journal of Electrical Engineering and Computer Science 15, no. 3 (2019): 1401. http://dx.doi.org/10.11591/ijeecs.v15.i3.pp1401-1410.

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<span>This paper presents the hardware design of a 2-dimensional Hadamard transform used the in the rate distortion optimization module in state-of-the-art HEVC video encoder. The transform is mainly used to quickly determine optimum block size for encoding part of a video frame. The proposed design is both scalable and fast by 1) implementing a unified architecture for sizes 4x4 to 32x32, and 2) pipelining and feed through control that allows high performance for all block sizes. The design starts with high-level algorithmic loop unrolling optimization to determine suitable level of par

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Shashidhar, A., and B. Ramesh K. "Design of Power Efficient and High Temperature Operational Priority Encoder." Journal of Advancement in Communication System 7, no. 3 (2024): 9–16. https://doi.org/10.5281/zenodo.12718734.

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<em>This research paper proposes a novel approach to designing a power-efficient and high-temperature operational priority encoder using Silicon Carbide (SiC) JFETs (Junction Field-Effect Transistors) and Carbon Nanotube Field-Effect Transistors (CNFETs).[1] The proposed priority encoder leverages the superior thermal stability and low power consumption characteristics of SiC JFETs and CNFETs to achieve reliable performance in extreme environments. </em><em>The proposed priority encoder architecture is meticulously designed to harness the inherent characteristics of SiC JNFET and CNTFETs, expl

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Gao, Bingshu, Dongdong Yu, Gong Chen, and Wei Lu. "Online Calibration Based on Laser-Encoder Odometry." Journal of Physics: Conference Series 2520, no. 1 (2023): 012041. http://dx.doi.org/10.1088/1742-6596/2520/1/012041.

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Abstract This paper proposes a new online calibration method for the differential-drive mobile robot equipped with a laser scanner. Our algorithm can jointly estimate the 3-DoF extrinsic parameters of the laser scanner and the intrinsic parameters (radii and wheel spacing) of the differential-drive kinematic model. Applying the pre-integration theory initially developed the for IMU sensor to the differential-drive kinematic model, we adopt iterative nonlinear optimization to minimize the cost derived from laser and encoder measurements. Experiments results confirm that the proposed method can

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Yu, Junchi, Tingyang Xu, Yu Rong, Junzhou Huang, and Ran He. "Structure-aware conditional variational auto-encoder for constrained molecule optimization." Pattern Recognition 126 (June 2022): 108581. http://dx.doi.org/10.1016/j.patcog.2022.108581.

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Chunlian, Yao, Liu Wen, Wu hongli, Mao Dianhui, and Liu Li. "Bit Rate Buffer Control and Optimization of Embedded Video Encoder." Open Cybernetics & Systemics Journal 8, no. 1 (2014): 1009–14. http://dx.doi.org/10.2174/1874110x01408011009.

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35

Li, Shujie, Haisheng Zhu, Lei Wang, and Xiaoping Liu. "Dual auto-encoder network for human skeleton motion data optimization." Journal of Image and Graphics 27, no. 4 (2022): 1277–89. http://dx.doi.org/10.11834/jig.200780.

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Xu, Long, Sam Kwong, Yun Zhang, and Debin Zhao. "Low-Complexity Encoder Framework for Window-Level Rate Control Optimization." IEEE Transactions on Industrial Electronics 60, no. 5 (2013): 1850–58. http://dx.doi.org/10.1109/tie.2012.2190960.

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Liu, Hongjian. "Research on Literary Translation Based on the Improved Optimization Model." Discrete Dynamics in Nature and Society 2022 (April 16, 2022): 1–7. http://dx.doi.org/10.1155/2022/1329632.

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Machine translation is widely used in people’s daily lives and production, occupying an important position. In order to improve the accuracy of the literary intelligent translation, research on literary intelligent translation is based on the improved optimization model. Based on semantic features, the semantic ontology optimization model including an encoder and a decoder is created by machine translation. In order to improve the accuracy of the intelligent translation literature of the semantic ontology optimization model, the conversion layer, including the forward neural network layer, res

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Chang, Syuan-Cheng, Chung-Ping Chang, and Yung-Cheng Wang. "Development and Optimization of a Differential Signal-Based Fabry-Perot Interferometer for Nanopositioning." Tehnički glasnik 19, no. 3 (2025): 417–21. https://doi.org/10.31803/tg-20240514145648.

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In this study, we present the optimization of a Fabry-Perot interferometer with a differential signal utilized as the laser encoder to meet the stringent demands of nanopositioning. The proposed system aims to enhance stability and accuracy in nanopositioning applications by leveraging the common path structure and coaxial characteristics of Fabry-Perot interferometers. To improve the resolution of this system, an interpolation module is employed to increase the laser encoder resolution to 15.82 nm. Compared to the simulated interference signal from traditional Fabry-Perot interferometers, the

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Yang, Xi, Jie Zhang, Han Fang, et al. "AutoStegaFont: Synthesizing Vector Fonts for Hiding Information in Documents." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 3 (2023): 3198–205. http://dx.doi.org/10.1609/aaai.v37i3.25425.

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Hiding information in text documents has been a hot topic recently, with the most typical schemes of utilizing fonts. By constructing several fonts with similar appearances, information can be effectively represented and embedded in documents. However, due to the unstructured characteristic, font vectors are more difficult to synthesize than font images. Existing methods mainly use handcrafted features to design the fonts manually, which is time-consuming and labor-intensive. Moreover, due to the diversity of fonts, handcrafted features are not generalizable to different fonts. Besides, in pra

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Li, Yibiao. "Optimization of Artistic Image Segmentation Algorithm Based on Feed Forward Neural Network under Complex Background Environment." Journal of Environmental and Public Health 2022 (September 13, 2022): 1–11. http://dx.doi.org/10.1155/2022/9454344.

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Based on the theory and application, this paper discusses the optimization of art image segmentation algorithm based on FFNN (Feed Forward Neural Network). In this paper, residual units are used in the corresponding stages of encoder and decoder, and feature information of several convolution layers in each convolution stage of encoder is extracted at the same time. And the feature pyramid module is used to extract multiscale features from the feature map of the last convolution stage in the encoder. Finally, pixel by pixel additions combine the previously mentioned feature information into th

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Park, Youngki, and Youhyun Shin. "Adaptive Bi-Encoder Model Selection and Ensemble for Text Classification." Mathematics 12, no. 19 (2024): 3090. http://dx.doi.org/10.3390/math12193090.

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Can bi-encoders, without additional fine-tuning, achieve a performance comparable to fine-tuned BERT models in classification tasks? To answer this question, we present a simple yet effective approach to text classification using bi-encoders without the need for fine-tuning. Our main observation is that state-of-the-art bi-encoders exhibit varying performance across different datasets. Therefore, our proposed approaches involve preparing multiple bi-encoders and, when a new dataset is provided, selecting and ensembling the most appropriate ones based on the dataset. Experimental results show t

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Guo, Hao, Meichao Song, Zhen Ding, Chunzhi Yi, and Feng Jiang. "Vision-Based Efficient Robotic Manipulation with a Dual-Streaming Compact Convolutional Transformer." Sensors 23, no. 1 (2023): 515. http://dx.doi.org/10.3390/s23010515.

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Learning from visual observation for efficient robotic manipulation is a hitherto significant challenge in Reinforcement Learning (RL). Although the collocation of RL policies and convolution neural network (CNN) visual encoder achieves high efficiency and success rate, the method general performance for multi-tasks is still limited to the efficacy of the encoder. Meanwhile, the increasing cost of the encoder optimization for general performance could debilitate the efficiency advantage of the original policy. Building on the attention mechanism, we design a robotic manipulation method that si

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Wang, Lei, Xin Wei, Pengbo Liang, Yongde Zhang, and Shuanghui Hao. "A Novel Angle Segmentation Method for Magnetic Encoders Based on Filtering Window Adaptive Adjustment Using Improved Particle Swarm Optimization." Sensors 23, no. 21 (2023): 8695. http://dx.doi.org/10.3390/s23218695.

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In this paper we outline newly-developed control algorithms, designed to achieve high-precision feedback for a motor control system using a magnetic encoder. The magnetic encoder, combing single-pole and multi-pole magnetic steels, was adopted to extend the resolution of the magnetic encoder. First, with a view to settling the issue of the jump points of the multi-pole angle value at the convergence of two adjacent magnetic poles, the angle segmentation method, which uses the window filter discrimination method, is employed to determine the actual angle value. The appropriate filter window wid

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Abdulaziz AlArfaj, Abeer, and Hanan Ahmed Hosni Mahmoud. "A Moving Object Tracking Technique Using Few Frames with Feature Map Extraction and Feature Fusion." ISPRS International Journal of Geo-Information 11, no. 7 (2022): 379. http://dx.doi.org/10.3390/ijgi11070379.

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Moving object tracking techniques using machine and deep learning require large datasets for neural model training. New strategies need to be invented that utilize smaller data training sizes to realize the impact of large-sized datasets. However, current research does not balance the training data size and neural parameters, which creates the problem of inadequacy of the information provided by the low visual data content for parameter optimization. To enhance the performance of moving object tracking that appears in only a few frames, this research proposes a deep learning model using an abu

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Yin, Yijun, Wenzheng Xu, Lei Chen, and Hao Wu. "CoT-UNet++: A medical image segmentation method based on contextual transformer and dense connection." Mathematical Biosciences and Engineering 20, no. 5 (2023): 8320–36. http://dx.doi.org/10.3934/mbe.2023364.

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<abstract> <p>Accurate depiction of individual teeth from CBCT images is a critical step in the diagnosis of oral diseases, and the traditional methods are very tedious and laborious, so automatic segmentation of individual teeth in CBCT images is important to assist physicians in diagnosis and treatment. TransUNet has achieved success in medical image segmentation tasks, which combines the advantages of Transformer and CNN. However, the skip connection taken by TransUNet leads to unnecessary restrictive fusion and also ignores the rich context between adjacent keys. To solve these

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Yikui, He. "Optimization and Implementation of H.264 Encoder Based on DSP Platform." Journal of Physics: Conference Series 1982, no. 1 (2021): 012177. http://dx.doi.org/10.1088/1742-6596/1982/1/012177.

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You, Lei, Zhimin Gao, Yu Tong Han, and Xin Su. "Transmission Optimization of Wireless Visual Sensor Networks with Compressed Sensing Encoder." Applied Mechanics and Materials 263-266 (December 2012): 878–81. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.878.

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The design and optimization of wireless visual sensor network (WVSN) is challenging due to error-prone wireless link, limited resource and low computational capacity. Traditional video coding methods and layered transmission protocols are not efficient for visual information collection in WVSNs. In this paper, we adopted the compressed sensing (CS) paradigm to sense and encode the visual information, and proposed a cross-layer transmission algorithm to achieve optimal trade-off between total distortion and power consumption by simultaneously controlling the CS measurement rate and allocating t

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Lim, Duk-Gyu, Sharad Shakya, and Je-Hoon Lee. "Optimization of a Systolic Array BCH encoder with Tree-Type Structure." International Journal of Contents 9, no. 1 (2013): 33–37. http://dx.doi.org/10.5392/ijoc.2013.9.1.033.

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Zhang, Duo Li, Chuan Jie Wang, Yu Kun Song, Gao Ming Du, and Xian Wen Cheng. "Design and Memory Optimization of Motion Estimation Module for H.264/AVC Encoder." Advanced Materials Research 179-180 (January 2011): 1350–55. http://dx.doi.org/10.4028/www.scientific.net/amr.179-180.1350.

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H.264/AVC standard has been widely used in video compression at various kinds of application domain. Motion estimation takes the most calculation workload of H.264/AVC encoder. Memory optimization has played an even more important role in encoder design. Firstly, dependency relation between motion vectors was analyzed and removed at a little cost of estimation accuracy decrement, and then a 3-stage macro-block level pipeline architecture was proposed to increase parallel process ability of motion estimation. Then an optimized memory organization strategy of reference frame data was put forward

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Galdran, Adrian. "Polyp and Surgical Instrument Segmentation with Double Encoder-Decoder Networks." Nordic Machine Intelligence 1, no. 1 (2021): 5–7. http://dx.doi.org/10.5617/nmi.9107.

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This paper describes a solution for the MedAI competition, in which participants were required to segment both polyps and surgical instruments from endoscopic images. Our approach relies on a double encoder-decoder neural network which we have previously applied for polyp segmentation, but with a series of enhancements: a more powerful encoder architecture, an improved optimization procedure, and the post-processing of segmentations, based on tempered model ensembling. Experimental results show that our method produces segmentations that show a good agreement with manual delineations provided

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