tag: image classification

HW Implementation of Memristive ANNs
By Technical Paper Link - 22 Mar, 2024 - Comments: 0

A new technical paper titled "Hardware implementation of memristor-based artificial neural networks" was published by KAUST, Universitat Autònoma de Barcelona, IBM Research, USC, University of Michigan and others. Abstract: "Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL) techniques, which rely on networks of connected simple computing units oper... » read more

Embedded Automotive Platforms: Evaluating Power And Performance Of Image Classification And Objects Detection CNNs 
By Technical Paper Link - 16 Oct, 2023 - Comments: 0

A technical paper titled “Performance/power assessment of CNN packages on embedded automotive platforms” was published by researchers at University of Modena and Reggio Emilia. Abstract: "The rise of power-efficient embedded computers based on highly-parallel accelerators opens a number of opportunities and challenges for researchers and engineers, and paved the way to the era of edge com... » read more

Achieving Greater Accuracy In Real-Time Vision Processing With Transformers
By Gordon Cooper - 10 Jan, 2023 - Comments: 0

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications and got interesting results. While previously, vision tasks had been dominated by convolutional neural networks (CNNs), transformers have proven surprisingly adaptable to vision tasks like image cl... » read more

Multiexpert Adversarial Regularization For Robust And Data-Efficient Deep Supervised Learning
By Samsung - 16 Nov, 2022 - Comments: 0

Deep neural networks (DNNs) can achieve high accuracy when there is abundant training data that has the same distribution as the test data. In practical applications, data deficiency is often a concern. For classification tasks, the lack of enough labeled images in the training set often results in overfitting. Another issue is the mismatch between the training and the test domains, which resul... » read more

Fabs Drive Deeper Into Machine Learning
By Anne Meixner - 07 Sep, 2021 - Comments: 0

Advanced machine learning is beginning to make inroads into yield enhancement methodology as fabs and equipment makers seek to identify defectivity patterns in wafer images with greater accuracy and speed. Each month a wafer fabrication factory produces tens of millions of wafer-level images from inspection, metrology, and test. Engineers must analyze that data to improve yield and to reject... » read more

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