Related papers: A lightweight, user-configurable detector ASIC dig…
Applying image sensors in automation of Industrial Internet of Things (IIoT) technology is on the rise, day by day. In such companies, a large number of high volume images are transmitted at any moment; therefore, a significant challenge is…
We present a novel single-photon detector based on a vacuum tube incorporating a photocathode, a microchannel plate (MCP), and a Timepix4 CMOS ASIC functioning as a pixelated anode. Designed to handle photon rates up to 1 billion per second…
Diffusion-based image compression has recently shown outstanding perceptual fidelity, yet its practicality is hindered by prohibitive sampling overhead and high memory usage. Most existing diffusion codecs employ U-Net architectures, where…
Despite offering high sensitivity, a high signal-to-noise ratio, and a broad spectral range, single-pixel imaging (SPI) is limited by low measurement efficiency and long data-acquisition times. To address this, we propose a…
This paper presents a novel approach utilizing a scalable neural decoder application-specific integrated circuit (ASIC) based on metal oxide memristors in a 180nm CMOS technology. The ASIC architecture employs in-memory computing with…
The experiment of the future electron-positron colliders has unprecedented requirements on the vertex resolution, such as around 3micron single point resolution for the inner most detector layer, with fast readout, and very low…
Image compression, as one of the fundamental low-level image processing tasks, is very essential for computer vision. Tremendous computing and storage resources can be preserved with a trivial amount of visual information. Conventional…
We present an approach to fabrication and packaging of integrated photonic devices that utilizes waveguide and detector layers deposited at near-ambient temperature. All lithography is performed with a 365 nm i-line stepper, facilitating…
Digital cameras are commonly used for diagnostic purposes in large-scale physics experiments. A typical image diagnostic system consists of an optical setup, digital camera, frame grabber, image processing CPU, and data analysis tool. The…
In this thesis, we describe a new, practical approach to integrating hardware-based data compression within the memory hierarchy, including on-chip caches, main memory, and both on-chip and off-chip interconnects. This new approach is fast,…
LiDAR are increasingly being used in intelligent vehicles (IV) or intelligent transportation systems (ITS). Storage and transmission of data generated by LiDAR sensors are one of the most challenging aspects of their deployment. In this…
Modern scientific instruments operate under increasingly extreme constraints on bandwidth, latency, and power. Inference at the sensor edge determines experimental data collection efficiency by deciding which information to save for further…
The accelerating growth of global data generation demands data storage platforms that offer high capacity, long lifespan, and low energy consumption beyond the limits of electronic memory technologies. Optical storage provides an attractive…
We studied the properties of chromium compensated GaAs when coupled to charge integrating ASICs as a function of detector temperature, applied bias and x-ray tube energy. The material is a photoresistor and can be biased to collect either…
The design and evaluation on the NSLS-II beamline of the 3FI application specific integrated circuit (ASIC) bump-bonded to a simply, planar, two-dimensionally segmented silicon sensor is presented. The ASIC was developed for Full-Field…
Microarray technology is a new and powerful tool for the concurrent monitoring of a large number of gene expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence,…
Learned image compression has achieved extraordinary rate-distortion performance in PSNR and MS-SSIM compared to traditional methods. However, it suffers from intensive computation, which is intolerable for real-world applications and leads…
In this paper we propose a novel approach to model compression termed Architecture Compression. Instead of operating on the weight or filter space of the network like classical model compression methods, our approach operates on the…
Object detection in images has reached unprecedented performances. The state-of-the-art methods rely on deep architectures that extract salient features and predict bounding boxes enclosing the objects of interest. These methods essentially…
The physics aims at the proposed future CLIC high-energy linear $e^+ e^-$ collider pose challenging demands on the performance of the detector system. In particular the vertex and tracking detectors have to combine precision measurements…