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Cheng-Lin Tsao - IEEE Xplore Author Profile

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Nighttime image flare occurs due to light bending through the lens, creating a high contrast between bright light sources and dark backgrounds, which degrades image quality. To address this, we propose FBNet (Flare Basis Latent Space Transformation Network), a novel network designed for efficient nighttime flare removal. FBNet employs a mapping-based self-attention mechanism to detect and eliminat...Show More
Simultaneous Localization and Mapping (SLAM) is pivotal for autonomous robotics, yet feature-based SLAM systems struggle with sparse environmental representations and robustness under dynamic conditions. Optical-flow-based SLAM (OpF-SLAM) addresses these limitations by leveraging pixel-level motion data for dense mapping; however, its computational intensity hinders real-time deployment. This pape...Show More
This paper proposed an algorithm-hardware co-design of an event-driven spiking neural network (SNN) accelerator for classification tasks of event-based data from dynamic vision sensors (DVS), which can implement a feed-forward SNN with a maximum network size of 1 million synapses. Configurable structured sparsity is introduced between the first layer and the second layer to improve energy efficien...Show More
Motion artifacts (MA), common-mode interference (CMI), and varying electrode-tissue impedance (ETI) are the main factors that cause heart rate detection errors in practical wearable ECG acquisition. These problems are further exacerbated in two-electrode based ECG systems. This article presents an ambulatory ECG acquisition ASIC with fully integrated, low power motion artifacts removal (MAR) and h...Show More
Optical remote sensing images (RSIs) have received widespread attention in fields such as agricultural monitoring, mineral exploration, and military defense. However, the detection performance will be seriously degraded when interfered with by noise. To overcome this issue, we first present a novel method called tensor low-rank approximation (TLRA), which leverages the weighted tensor nuclear norm...Show More
While attention-based approaches have shown considerable progress in enhancing image fusion and addressing the challenges posed by long-range feature dependencies, their efficacy in capturing local features is compromised by the lack of diverse receptive field extraction techniques. To overcome the shortcomings of existing fusion methods in extracting multiscale local features and preserving globa...Show More
The Versatile Video Coding (VVC) standard notably enhances encoding efficiency with the Quad-Tree plus Multi-Type Tree (QTMTT) partition structure. However, the complex QTMTT tool presents substantial challenges in both software and hardware implementation. To overcome those challenges, this paper introduces a hardware-friendly partition decision algorithm for VVC intra and inter coding. Firstly, ...Show More
Personalized recommendation systems are massively deployed in production data centers. The memory-intensive embedding layers of recommendation systems are the crucial performance bottleneck, with operations manifesting as sparse memory lookups and simple reduction computations. Recent studies propose near-memory processing (NMP) architectures to speed up embedding operations by utilizing high inte...Show More
This brief designs and implements a 4-D imaging light detection and ranging (LiDAR) receiver. It employs a reconfigurable transimpedance amplifier (TIA) that alternates between two modes to separately achieve ranging and light intensity quantification functions. A new mode-switching method based on a monostable multivibrator is proposed, allowing the TIA to automatically switch modes during measur...Show More
This letter presents a hybrid, three-step zoom-linear-exponential incremental analog-to-digital converter (ZLE-IADC) for audio applications. The zoom-SAR in the first step provides coarse signal quantization and relaxes the accuracy requirements of subsequent conversions. The second step utilizes a single-loop, first-order delta–sigma modulator ( \Delta \Sigma M). In the third step, the $\Delt...Show More
Versatile Video Coding (VVC) employs Affine Motion Compensation (AMC) to process scenes with high-order motion. To improve AMC efficiency, the Affine Motion Estimation (AME) process based on the gradient-based iterative algorithm (GIA) and block match algorithm (BMA) is introduced to the VVC Test Model (VTM). However, the AME process is highly complex and difficult for hardware implementation in r...Show More
This article presents a tunnel magnetoresistance (TMR)-based magnetic sensor for contactless current sensing. The TMR readout circuit utilizes a current-balancing instrumentation amplifier (CBIA) with ping-pong auto-zeroing (PPAZ), achieving an integrated magnetic noise of 206 nTrms in a wide bandwidth of 2 MHz. Compared with chopping amplifiers, an auto-zeroed CBIA provides a ripple-free output, ...Show More
This article proposes a novel collaborative-flip synchronized switch harvesting on capacitors (CF-SSHCs) rectifier and multioutput synchronous dc-dc converters with shared capacitors. Compared to the traditional SSHC, our CF-SSHC rectifier can increase the number of flipping phases, potentially enhancing the flipping efficiency and output power under specific conditions where C_{\text {FLY}} i...Show More
Versatile video coding (VVC) introduces multi-type tree (MTT) and larger coding tree unit (CTU) to improve compression efficiency compared to its predecessor High Efficiency Video Coding (HEVC). This leads to higher throughput for fractional motion estimation (FME) to meet the needs of real-time processing. In this context, this article proposes an interpolation-free algorithm based on an error su...Show More
Neuromorphic computing has emerged as a revolutionary technology in consumer electronics, with computing-in-memory (CIM) attracting considerable attention for its potential to minimize data transfer. However, most CIM accelerators necessitate numerous digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) for mixed-signal data processing, resulting in substantial area and ener...Show More
Sparse linear discriminant analysis (LDA) is a popular machine learning method that improves the accuracy of data classification by introducing sparsity. However, its performance often degrades seriously when encountering noise. To address this issue, this paper proposes a new method called efficient and robust sparse linear discriminant analysis (ERSLDA). The core idea is to characterize the loca...Show More
In the field of computer vision, the acquired dataset usually contains a certain number of outliers and noise, which leads to errors in the estimated mathematical model. RANSAC estimates model parameters by randomly selecting a subset of the data, reducing the impact of these outliers and noise. However, for datasets with a high proportion of inliers, the traditional RANSAC has to perform a large ...Show More
Finding distinctions and connections between multiple visual targets through the detection of keypoints has become one of the research hot-spots in the field of computer vision. SIFT has received wide recognition and attention for its powerful performance in image match. However, the original SIFT has high complexity and time-consuming problems. In this paper, we propose Simple SIFT (S-SIFT), an i...Show More
Neural radiance field (NeRF) has proved to be promising in augmented/virtual-reality applications. However, the deployment of NeRF on edge devices suffers from inadequate throughput due to redundant ray sampling and congested memory access. To address these challenges, this article proposes Hi-NeRF, a multirendering-core accelerator for efficient edge NeRF rendering. On the architecture level, a h...Show More
In this paper, we consider the problem of estimating the angular parameters, i.e., the nominal angle-of-arrivals (AoAs) and angular spreads, of incoherently distributed sources using the phased-array equipped with a single RF chain. We first derive the approximate Fourier series of the received power. The coefficients can be expressed in closed form with the angular parameters. In the case of sing...Show More
A range of quantum-, optical- and CMOS-based approaches have been explored to solve Nondeterministic polynomial-time hard (NP-hard) combinatorial optimization problems (COPs), of which we consider ring oscillator (ROSC) coupled Ising machine to be highly prospective. This brief proposed a scalable ROSC-based Ising machine with capacity coupling and phase drift eliminator. The coupling module consi...Show More
Nowadays, with the increase resolution of Dynamic Vision Sensor (DVS), efficient compression algorithm for event stream is needed urgently. Conventional DVS system encodes event data in address event representation (AER) for output while ignores the data redundancy imposed by the correlation of events. To address this challenge, this paper first analyzes the spatiotemporal characteristics of event...Show More
This paper proposed a hardware-algorithm co-design of an event-driven Spiking Neural Network (SNN) accelerator with structured sparsity for Dynamic Vision Sensors (DVS) applications. The accelerator can accommodate up to 1024 neurons and 1 million synapses for a feed-forward fully connected SNN implementation. Configurable structured sparsity is introduced by modular arithmetic both in the algorit...Show More
The dataset for Video Coding for Machines (VCM) contains sensitive information that requires privacy preservation to address vulnerabilities. Achieving a balance to protect this sensitive data while maintaining VCM performance is crucial. We introduce an autoencoder integrated with a deep learning network that utilizes the ResNet architecture. This design blurs private details while preserving the...Show More
The promotion of the HEVC standard has significantly alleviated the burden of network transmission and video storage. However, its inherent complexity and data dependencies pose a significant challenge in achieving high compression efficiency hardware encoder. To tackle this challenge, we propose several hardware-oriented algorithms and achieve a hardware encoder supporting both intra and inter co...Show More