Pixel Layer Research Articles

Estimating Power, Performance, and Area for On-Sensor Deployment of AR/VR Workloads Using an Analytical Framework

Augmented Reality and Virtual Reality have emerged as the next frontier of intelligent image sensors and computer systems. In these systems, 3D die stacking stands out as a compelling solution, enabling in situ processing capability of the sensory data for tasks such as image classification and object detection at low power, low latency, and a small form factor. These intelligent 3D CMOS Image Sensor (CIS) systems present a wide design space, encompassing multiple domains (e.g., computer vision algorithms, circuit design, system architecture, and semiconductor technology, including 3D stacking) that have not been explored in-depth so far. This article aims to fill this gap. We first present an analytical evaluation framework, STAR-3DSim, dedicated to rapid pre-RTL evaluation of 3D-CIS systems capturing the entire stack from the pixel layer to the on-sensor processor layer. With STAR-3DSim, we then propose several knobs for PPA (power, performance, area) improvement of the Deep Neural Network (DNN) accelerator that can provide up to 53%, 41%, and 63% reduction in energy, latency, and area, respectively, across a broad set of relevant AR/VR workloads. Last, we present full-system evaluation results by taking image sensing, cross-tier data transfer, and off-sensor communication into consideration.

The ATLAS experiment at the CERN Large Hadron Collider: a description of the detector configuration for Run 3

The ATLAS detector is installed in its experimental cavern at Point 1 of the CERN Large Hadron Collider. During Run 2 of the LHC, a luminosity of ℒ = 2 × 1034 cm-2 s-1 was routinely achieved at the start of fills, twice the design luminosity. For Run 3, accelerator improvements, notably luminosity levelling, allow sustained running at an instantaneous luminosity of ℒ = 2 × 1034 cm-2 s-1, with an average of up to 60 interactions per bunch crossing. The ATLAS detector has been upgraded to recover Run 1 single-lepton trigger thresholds while operating comfortably under Run 3 sustained pileup conditions. A fourth pixel layer 3.3 cm from the beam axis was added before Run 2 to improve vertex reconstruction and b-tagging performance. New Liquid Argon Calorimeter digital trigger electronics, with corresponding upgrades to the Trigger and Data Acquisition system, take advantage of a factor of 10 finer granularity to improve triggering on electrons, photons, taus, and hadronic signatures through increased pileup rejection. The inner muon endcap wheels were replaced by New Small Wheels with Micromegas and small-strip Thin Gap Chamber detectors, providing both precision tracking and Level-1 Muon trigger functionality. Trigger coverage of the inner barrel muon layer near one endcap region was augmented with modules integrating new thin-gap resistive plate chambers and smaller-diameter drift-tube chambers. Tile Calorimeter scintillation counters were added to improve electron energy resolution and background rejection. Upgrades to Minimum Bias Trigger Scintillators and Forward Detectors improve luminosity monitoring and enable total proton-proton cross section, diffractive physics, and heavy ion measurements. These upgrades are all compatible with operation in the much harsher environment anticipated after the High-Luminosity upgrade of the LHC and are the first steps towards preparing ATLAS for the High-Luminosity upgrade of the LHC. This paper describes the Run 3 configuration of the ATLAS detector.

Outer Barrel services chain characterisation for the ATLAS ITk Pixel detector

For the high-luminosity upgrade of the ATLAS Inner Tracking detector of the ATLAS experiment, a new pixel detector will be installed to allow for a bigger bandwidth and cope with the increased radiation among other challenges. This contribution will present the evaluation of the Outer Barrel Pixel layer services chains. A full data transmission study covering data merging will be presented from the pixel module all the way to the FELIX data acquisition system, using most of the components foreseen for the detector. Challenges and results of the services chain of the Outer Barrel will be highlighted.

Design and first experience of the prototype pixel layers for the ALICE FoCal

The University of Bergen is involved in developing two calorimeters: the pixel section of the Electromagnetic Forward Calorimeter for the ALICE Upgrade to be installed during LS3 for data-taking in the period 2029–2032 and the Digital Tracking Calorimeter for the proton Computed Tomography prototype. Both designs utilize pixel sensors and require a reliable connection to the readout which is positioned approximately 5 meters away. Furthermore, the structural design of these calorimeters calls for a compact layer assembly. This paper provides the strategies deployed to meet these critical requirements, focusing on the implementation of the chip-on-flex assembly, and the ultrasonic welding techniques. It further describes other design considerations essential for maintaining good signal integrity. Finally, it gives insight into the experiences and challenges faced while working with the prototypes, both in the laboratory and test beam setups.

Notice of Violation: A Dual-Band Beam Steering Multifunctional Reconfigurable Antenna Optimized by Non-Dominated Sorting Genetic Algorithm (NSGA-II) for Wi-Fi 6 Applications

Notice of Violation <br><br>“A Dual-Band Beam Steering Multifunctional Reconfigurable Antenna Optimized by Non-Dominated Sorting Genetic Algorithm (NSGA-II) for Wi-Fi 6 Applications” <br> by Junlin Pu, Bing Zhang, Yanping Zhou, Kama Huang, Tiancang Zhang, and Juan Yang <br> published in the IEEE Transactions on Antennas and Propagation, Digital Object Identifier: 10.1109/TAP.3209180 <br><br>The authors of this paper violated the IEEE’s Publication Principles. An author name was included in the Early Access version of this paper who did not contribute to the work and was added without their consent. The non-contributing author’s name has been removed <br><br> <br/> A design and optimization method to realize a beam steering multi-functional reconfigurable antenna (MRA) working at two independent frequencies with an octave range frequency span is proposed. While the conventional MRAs (multi-functional reconfigurable antennas) have lacked frequency reconfigurability, the proposed design and optimization method manage to realize a beam steering MRA at two operating frequencies. To verify, a dual-band beam steering MRA working at 2.45 GHz and 5.3 GHz is designed to be compatible with the IEEE 802.11 ax for Wi-Fi 6 applications. The proposed MRA consists of a feed layer, a dual-band aperture-coupled driven patch, and a parasitic pixel layer. The driven patch is designed to ensure sufficient coupling with the parasitic layer at both two frequencies. The parasitic layer consists of a 6×6 planar array of rectangular pixels interconnected by positive-intrinsic-negative (PIN) diode switches. By optimizing the switches’ modes with the non-dominated sorting genetic algorithm (NSGA-II), the MRA’s beams are regulated at directions of θ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">_xz</i> =0°, ±30° for both 2.45 GH and 5.3 GHz. This work manages to explore the potential of the traditional MRA for frequency reconfigurability applications, besides its widely-reported radiation pattern reconfigurability. The proposed MRA is a capable candidate as a Wi-Fi 6 router antenna. The design and optimization method of the MRA based on NSGA-II by Python are summarized systematically in an easy-to-follow manner, which is instructive for MRA designers.

Image encryption algorithm based on hyperchaotic system and dynamic DNA encoding

Since the existing DNA encryption algorithms only have fixed DNA coding and decoding rules and a single algorithm that cannot meet more complex and more secure encryption requirements, an image encryption algorithm based on hyperchaotic system and dynamic DNA coding is proposed. The algorithm proposes two new operation methods in the DNA operation rules, namely the equal-additive column transformation and the equal-subtractive column transformation. which combine the SHA-256 function and the external key to generate the initial value of the chaotic system to ensure that key and plaintext of algorithm are correlated. In the encryption process, the plaintext image is firstly converted into a two-dimensional matrix for rotation and scrambling. Then the chaotic sequence generated by the hyperchaotic Chen system is used to perform DNA dynamic encoding, decoding and operation on the scrambled matrix and block matrix generated by logistic chaotic sequence. Finally, the encrypted matrix is scrambled in one dimension. Simulation results show that the improved encryption algorithm has a larger key space, breaks the strong correlation between image pixel layers, and can effectively resist multiple attacks.

Color Processing System of Art Color Based on Fractional Differential Equation

Abstract This paper mainly studies a high-precision correction method for warp knitting seamless images. The color factor conversion method is used to transform the gray level of the center point in the frequency domain. Then this paper proposes an image-denoising method based on an average way to improve image quality. The multichannel scalar channel is solved using the gradient domain method, and the fractional differential equations of two images are given. A structure tensor matrix is constructed to describe the geometric properties of images. The regional contrast of the image is calculated by using the characteristics of adjacent layers of pixels. The fusion of multiple images is based on the limitations of object functionality. This can make the texture structure of artistic color pictures more obvious. The experiment of color restoration shows that this method has a good interpretation effect. The color image processing technique has obtained an excellent restoration effect.

73‐3: A Study on WAD Improvement of a large size AMOLED panel

In this work, the WAD Characteristics were improved by forming a concave‐convex scattering structure on the organic planarization layer of large size AMOLED backplane TFT. By using a slit mask of the scanner as a VIA mask on the photosensitive poly‐imide organic planarization film, a semi‐transmissive area and a contact hole were made simultaneously without adding a separate photo process to form a concave‐convex scattering structure. On top of that, ITO/Ag/ITO anode pixel, EL and cathode layers were sequentially formed to improve WAD Characteristics of the top emitting AMOLED panel. Confirming the effect of WAD improvement and reduction of frontal luminance when forming a concave‐convex structure from the existing EL Spectrum through simulation, angle of concave‐convex structure is 10~15° to satisfy the conditions of 30% improvement in WAD, 5% drop in frontal luminance, 40‐50% of Concave‐convex structure area ratio in the planarization film was derived. As a result of fabricating a large size AMOLED top emitting panel, when Concave‐convex scattering angle of 5 ~ 12° is formed, WAD 10~24% improvement and frontal luminance drop within 5% can be seen. it was possible to confirm uniformly improved WAD value within Δu'v' 0.014 ~ 0.018 at the center/edge 9 Points compared to the normal panel.

Design and Optimization of a High-Gain Filtering Antenna Based on Parasitic Pixel Layer

A novel high-gain filtering antenna based on the parasitic pixel layer is designed and optimized in this paper. Initially, a circular patch surrounded by a shorted concentric annular ring one is proposed as the radiation source, such a design is able to realize an upper radiation null. Afterward, a parasitic pixel layer is placed upon the radiation source with an air gap. Another radiation null at the lower band is then obtained by optimizing the connection status between adjacent pixel elements based on the internal multi-port method. Besides that, the parasitic pixel layer can enhance the realized broadside gain. Finally, a high-gain filtering antenna with a bandpass response is obtained. The antenna is validated by a full-wave simulation study followed by the experimental verification. Measured results indicate that the antenna can operate from 4.7 to 5.4 GHz with an average gain of 9.6 dBi and two radiation nulls at the lower and upper band edges of the reflection coefficient curve.

Design and characterisation of a new FoCal-E prototype for ALICE experiment

The FoCal-E detector is a part of the FoCal detector aiming to provide unique capabilities to measure small-x gluon distributions via prompt photon production. It represents an upgrade to the ALICE experiment, and will be installed during LS3 for data taking in 2029–2032 at the LHC. This detector is composed of a silicon and tungsten sampling calorimeter hybrid design combining two different Si (Silicon) readout technologies: Pad layers and Pixel layers. In this paper, we focus on the development of readout electronics, the concept of its design and the solution proposed to solve the grounding issue encountered during the first SPS test beam at CERN in September 2021.

Computational research on flat image design and style based on perceptual feature quantification

Abstract In order to solve the problem that a large number of low-value and easy-to-consume graphic designs consume the human and financial resources of the society and also waste the inherent value of design resources, by dividing the layers of pixels, elements, relations, planes and applications, this article defines the corresponding feature representations and studies related methods for quantifying geometric features, perceptual features and style features. The content includes the extraction method of element colour, the calculation method of layout-aware feature and colour-match-aware feature, and the pairwise comparison method of style feature. The experimental results show that the method proposed in this article has lower complexity and is significantly better than other algorithms. Comparing the method proposed in this article with other methods, the average time of this algorithm is 2.6 s under the condition of guaranteed images. The study of the design feature-driven graphic image style calculation method is not only of great significance for solving repeated design problems but also provides a basis and reference for the future development of intelligent design.

Foreground-Aware Refinement Network for Building Extraction from Remote Sensing Images

To extract buildings accurately, we propose a foreground-aware refinement network for building extraction. In particular, in order to reduce the false positive of buildings, we design the foreground-aware module using the attention gate block, which effectively suppresses the features of nonbuilding and enhances the sensitivity of the model to buildings. In addition, we introduce the reverse attention mechanism in the detail refinement module. Specifically, this module guides the network to learn to supplement the missing details of the buildings by erasing the currently predicted regions of buildings and achieves more accurate and complete building extraction. To further optimize the network, we design hybrid loss, which combines BCE loss and SSIM loss, to supervise network learning from both pixel and structure layers. Experimental results demonstrate the superiority of our network over state-of-the-art methods in terms of both quantitative metrics and visual quality.

Prototyping serial powering with RD53A

The ATLAS inner detector will be replaced by an all-silicon detector for the HL-LHC upgrade around 2025. The innermost five layers of the detector system will be pixel detector layers which will be most challenging in terms of radiation hardness, data rate and readout speed. A serial power scheme will be used for the pixel layers to reduce the material budget and power consumption in cables. New elements are required to operate and monitor a serially powered detector including a detector control system, constant current sources and front-end electronics with shunt regulators. Prototypes for all sections of the ITk pixel detector are built to verify the concept and operate multiple serial power chains as a system test. The evaluation of both the readout of multi-modules and mechanical integration are further aims of the prototyping campaign. In the contribution, results will be presented of this prototyping effort. Moreover, details and features of serial powering for full detector systems will be given.

CMS Phase-1 pixel detector refurbishment during LS2 and readiness towards the LHC Run 3

The CMS Phase-1 pixel detector was extracted from the underground cavern after the end of the LHC Run 2 in 2019 and has been kept cold to protect the silicon sensors during the long shutdown period (LS2) in 2019–2021. The LHC is now preparing for the next period of data taking, Run 3, which is scheduled to start in spring 2022. The Phase-1 pixel detector was going through a series of refurbishment and repairs this year to improve the quality of the collected data and enhance the detector performance. The innermost barrel pixel layer has been replaced with new modules and features improved front-end readout chips (PROC600v4), token bit manager chips (TBM10d), and circuit boards to rectify the issues discovered in Run 2. The forward pixel detector has been equipped with new cooling inlets for safe handling and features a revised high-voltage power distribution scheme to better match the low-voltage granularity. All the DC-DC converter modules have been replaced with new modules featuring an improved FEAST2.3 ASIC, which is considerably more robust against the total ionizing dose effect and thus prevents them from breaking during operation. Overall, this article will summarize the refurbishment work of the pixel detector during LS2, and highlight the readiness towards the LHC Run 3 after installation and commissioning.

A low-power high-quality CMOS image sensor using 1.5 V 4T pinned photodiode and dual-CDS column-parallel single-slope ADC

This paper presents a low-power high-quality CMOS image sensor (CIS) using 1.5 V 4T pinned photodiode (4T-PPD) and dual correlated double sampling (dual-CDS) column-parallel single-slope ADC. A five-finger shaped pixel layer is proposed to solve image lag caused by low-voltage 4T-PPD. Dual-CDS is used to reduce random noise and the nonuniformity between columns. Dual-mode counting method is proposed to improve circuit robustness. A prototype sensor was fabricated using a 0.11 µm CMOS process. Measurement results show that the lag of the five-finger shaped pixel is reduced by 80% compared with the conventional rectangular pixel, the chip power consumption is only 36 mW, the dynamic range is 67.3 dB, the random noise is only 1.55 e– rms, and the figure-of-merit is only 1.98 e–·nJ, thus realizing low-power and high-quality imaging.

A 1-μW Radiation-Hard Front-End in a 0.18-μm CMOS Process for the MALTA2 Monolithic Sensor

In this article, a low-power, radiation-hard front-end circuit for monolithic pixel sensors, designed to meet the requirements of low noise and low pixel-to-pixel variability, the key features to achieve high detection efficiencies, is presented. The sensor features a small collection electrode to achieve a small capacitance (<5 fF) and allows full CMOS in-pixel circuitry. The circuit is implemented in the 180-nm CMOS imaging technology from the TowerJazz foundry and integrated into the MALTA2 chip, which is part of a development that targets the specifications of the outer pixel layer of the ATLAS Inner Tracker upgrade at the LHC. One of the main challenges for monolithic sensors is a radiation hardness up to 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">15</sup> 1-MeV <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text {n}_{\text {eq}}/\text {cm}^{{2}}$ </tex-math></inline-formula> non-ionizing energy loss (NIEL) and 80 Mrad total ionizing dose (TID) required for this application. Tests up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${3} \cdot {10}^{15}$ </tex-math></inline-formula> 1-MeV <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text {n}_{\text {eq}}/\text {cm}^{{2}}$ </tex-math></inline-formula> and 100 Mrad were performed on the MALTA2 sensor and front-end circuit, which still show good performance even after these levels of irradiation, promising for even more demanding applications such as the future experiments at the high-luminosity large hadron collider (HL-LHC).

Design of a preclinical PET DOI detector module according to the reflector application area of the scintillation pixels

To measure the depth of interaction, we used two layers of scintillation pixels and a silicon photomultiplier (SiPM) to design a detector, and a DETECT2000 simulation was conducted to evaluate its performance. All surfaces of the scintillation pixels of the bottom layer were treated with a reflector except for the part that was optically connected to the SiPM or the scintillation pixels of the top layer. In addition, a reflector was partially applied to the scintillation pixels of the top layer. This design allows light to travel to other scintillation pixels through the area where no reflectors are applied so that the images of the scintillation pixels are formed at different points for each layer in the planar image. A gamma-ray reaction was generated at the center of each layer to obtain planar images, and the depth of interaction was measured. In addition, by measuring the intervals between the peaks at the point where the image of scintillation pixels was formed, we evaluated the depth of interaction according to the length of the area to which the reflector had not been applied. Due to the area of the scintillation pixel of the top layer that was not treated with the reflector, the depth of interaction could be measured in three layers. When this detector module is used for preclinical positron emission tomography (PET), the spatial resolution on the edges of the detection field of view can be improved by measuring the depth of interaction.

Novel 3D Pixel Sensors for the Upgrade of the ATLAS Inner Tracker

The ATLAS experiment will undergo a full replacement of its inner detector to face the challenges posed by the High Luminosity upgrade of the Large Hadron Collider (HL-LHC). The new Inner Tracker (ITk) will have to deal with extreme particle fluences. Due to its superior radiation hardness the 3D silicon sensor technology has been chosen to instrument the innermost pixel layer of ITk, which is the most exposed to radiation damage. Three foundries (CNM, FBK, and SINTEF), have developed and fabricated novel 3D pixel sensors to meet the specifications of the new ITk pixel detector. These are produced in a single-side technology on either Silicon On Insulator (SOI) or Silicon on Silicon (Si-on-Si) bonded wafers by etching both n- and p-type columns from the same side. With respect to previous generations of 3D sensors they feature thinner active substrates and smaller pixel cells of 50 × 50 and 25 × 100 µm2. This paper reviews the main design and technological issues of these novel 3D sensors, and presents their characterization before and after exposure to large radiation doses close to the one expected for the innermost layer of ITk. The performance of pixel modules, where the sensors are interconnected to the recently developed RD53A chip prototype for HL-LHC, has been investigated in the laboratory and at beam tests. The results of these measurements demonstrate the excellent radiation hardness of this new generation of 3D pixel sensors that enabled the project to proceed with the pre-production for the ITk tracker.

Road Detection Method based on Online Learning

Road detection is always the key problem of re-searches on areas of unmanned ground vehicle and computer vision. A road detection method is proposed based on online learning and multi-sensor fusion. First of all, the Lidar point clouds are projected onto the images via the joint calibration of these two kinds of sensors. Then Simple Linear Iterative Clustering is used to segment images into many superpixles. Based on that, a multilayer online learning method is proposed, in which 2 Support Vector Machines are trained to detect the road. To be specific, the superpixel layer Support Vector Machine is used to detect road roughly, and the pixel layer Support Vector Machine is then trained to classify the edge pixels of the road areas, which is classified by the upper-layer Support Vector Machine. These 2 Support Vector Machines are updated online at each frame to be adapted to the changing environment. At last, some experiments are carried out on KITTI RAW dataset and an autonomous land vehicle, and the results show the effectiveness of proposed method. The main contributions of this work lie on as follows: 1) a multilayer learning model is proposed to detect road more robustly and accurately; 2) an online learning method is proposed which can be adapted to the changing environment.

A Novel Color Image Encryption Algorithm Based on Three-Dimensional Chaotic Maps and Reconstruction Techniques

In the paper, a novel color image encryption scheme is proposed by use of the three-dimensional chaotic maps and some data reconstruction techniques. In the diffusion process of the encryption algorithm, the three-dimensional chaotic Logistic map is introduced to changes the pixel value of the plain image. Meanwhile, in the confusion process, the three-dimensional chaotic Cat map is applied to deal with the position of the image pixels. Moreover, some data reconstruction techniques are employed for the better encryption result. Furthermore, the corresponding decryption algorithm is also given. The significant advantages of our method are the effectiveness and simplicity, and our proposed method breaks the correlation between image pixel layers, offers a large key space and against differential and statistical attacks effectively. Finally, the superiority of the proposed algorithm will be shown by the experimental results, security analysis, and the corresponding comparisons with literature.