tag: deep learning

Expedera: Custom Deep Learning Accelerators Through Soft-IP
By Zoya Hasan - 06 Apr, 2022 - Comments: 0

Internet of Things (IoT) and Artificial Intelligence (AI) have caused a massive increase in data generation — and along with it, a need to process data faster and more efficiently. Dubbed a “tsunami of data,” data centers are expected to consume about one-fifth of worldwide energy before 2030. This data explosion is driving a wave of startups looking to gain a foothold in custom accele... » read more

Survey: 2022 Deep Learning Applications
By eBeam Initiative - 16 Mar, 2022 - Comments: 0

The 2022 member list of deep learning projects and products that eBeam members are working on in photomask to wafer semiconductor manufacturing. Participating companies include Advantest, ASML, Canon, CEA-LETI, D2S, Fraunhofer IPMS, Hitachi High-Tech Corporation, imec, NuFlare Technology, Siemens Industries Software, Inc.; Siemens EDA, STMicroelectronics, and TASMIT. Click here to see the su... » read more

The Right Project Is Key For Photomask Adoption Of Deep Learning
By Jan Willis - 17 Feb, 2022 - Comments: 0

Deep learning (DL) has become an integral part of the success of many companies. There have been many papers and some reported successes in semiconductor manufacturing, yet only 22% of the luminaries participating in the 2021 eBeam Initiative Luminaries survey see DL as a competitive advantage for photomask making by next year, as shown in figure 1. Looking at that chart, the luminaries believe... » read more

Multi-Task Network Pruning and Embedded Optimization for Real-time Deployment in ADAS
By Technical Paper Link - 15 Feb, 2022 - Comments: 0

Abstract: "Camera-based Deep Learning algorithms are increasingly needed for perception in Automated Driving systems. However, constraints from the automotive industry challenge the deployment of CNNs by imposing embedded systems with limited computational resources. In this paper, we propose an approach to embed a multi- task CNN network under such conditions on a commercial prototy... » read more

Enhancement of Robustness in Object Detection Module for Advanced Driver Assistance Systems
By Technical Paper Link - 07 Feb, 2022 - Comments: 0

Abstract: "A unified system integrating a compact object detector and a surrounding environmental condition classifier for enhancing the robustness of object detection scheme in advanced driver assistance systems (ADAS) is proposed in this paper. ADAS are invented to improve traffic safety and effectiveness in autonomous driving systems where object detection plays an extremely important rol... » read more

Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices
By Technical Paper Link - 20 Dec, 2021 - Comments: 0

Abstract:  "Recent advances in deep learning have been driven by ever-increasing model sizes, with networks growing to millions or even billions of parameters. Such enormous models call for fast and energy-efficient hardware accelerators. We study the potential of Analog AI accelerators based on Non-Volatile Memory, in particular Phase Change Memory (PCM), for software-equivalent accurate i... » read more

Deep Learning Delivers Fast, Accurate Solutions For Object Detection In The Automated Optical Inspection Of Electronic Assemblies
By Charlie Zhu - 07 Dec, 2021 - Comments: 0

When automated optical inspection (AOI) works, it is almost always preferable to human visual inspection. It can be faster, more accurate, more consistent, less expensive, and it never gets tired. However, some tasks that are very simple for humans are quite difficult for machines. Object detection is an example. For example, shown an image containing a cat, a dog, and a duck, a human can insta... » read more

Case Study — Deep Learning For Corner Fill Inspection And Metrology On Integrated Circuits
By CyberOptics - 07 Dec, 2021 - Comments: 0

CyberOptics utilized deep learning to accurately inspect the corner fill on integrated circuits (ICs) produced by a large memory supplier. Traditional methods of inspection showed limitations in their ability to entirely detect the presence and absence of fill, indicating that a more advanced approach was necessary. CyberOptics drew on its large pool of algorithm and neural network expertise to... » read more

Accelerating Inference of Convolutional Neural Networks Using In-memory Computing
By Technical Paper Link - 09 Nov, 2021 - Comments: 0

Abstract: "In-memory computing (IMC) is a non-von Neumann paradigm that has recently established itself as a promising approach for energy-efficient, high throughput hardware for deep learning applications. One prominent application of IMC is that of performing matrix-vector multiplication in (1) time complexity by mapping the synaptic weights of a neural-network layer to the devices of an ... » read more

Enablers And Barriers For Connecting Diverse Data
By Anne Meixner - 09 Nov, 2021 - Comments: 0

More data is being collected at every step of the manufacturing process, raising the possibility of combining data in new ways to solve engineering problems. But this is far from simple, and combining results is not always possible. The semiconductor industry’s thirst for data has created oceans of it from the manufacturing process. In addition, semiconductor designs large and small now ha... » read more

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