Affordance detection in computer vision allows segmenting an object into parts according to functions that those parts afford. Most solutions for affordance detection are developed in robotics using deep learning architectures that require substantial computing power. Therefore, these approaches are not convenient for application in embedded...
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2021 (v1)PublicationUploaded on: October 11, 2023
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2022 (v1)Publication
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2023 (v1)Publication
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2022 (v1)Publication
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2024 (v1)Publication
Hardware-aware neural architecture search (HW-NAS) allows the integration of convolutional neural networks (CNNs) in microcontrollers devices by automatically designing neural architectures that can fit prearranged hardware constraints. However, state-of-the-art HW-NAS target high-performance microcontrollers, whose power consumption does not...
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2022 (v1)Publication
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2023 (v1)Publication
This paper presents a novel method enabling point-of-care testing of thiocyanate concentration in saliva. Thiocyanate is an important biological marker; its levels are linked with diseases such as cancer and neurodegeneration. Hence, monitoring this marker frequently can positively impact users' lives. In the proposed setup, the goal is a...
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2022 (v1)Publication
This letter presents a low-cost, lightweight, and automatic readout system for accurate quantification of cisplatin (Cis-Pt) level in a colorimetric POC device. The system relies on an RGB camera to record the color changes in the test tube and an inference function trained via machine learning techniques to estimate Cis-Pt concentration. A...
Uploaded on: February 14, 2024