Browsing by Author "Caro Roca, Martí"
Now showing items 1-7 of 7
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An automotive case study on the limits of approximation for object detection
Caro Roca, Martí; Tabani, Hamid; Abella Ferrer, Jaume; Moll Echeto, Francisco de Borja; Morancho Llena, Enrique; Canal Corretger, Ramon; Altet Sanahujes, Josep; Calomarde Palomino, Antonio; Cazorla Almeida, Francisco Javier; Rubio Romano, Antonio; Fontova Muste, Pau; Fornt Mas, Jordi (2023-05)
Article
Restricted access - publisher's policyThe accuracy of camera-based object detection (CBOD) built upon deep learning is often evaluated against the real objects in frames only. However, such simplistic evaluation ignores the fact that many unimportant objects ... -
An energy-efficient GeMM-based convolution accelerator with on-the-fly im2col
Fornt Mas, Jordi; Fontova Muste, Pau; Caro Roca, Martí; Abella Ferrer, Jaume; Moll Echeto, Francisco de Borja; Altet Sanahujes, Josep; Studer, Christoph (2023-11)
Article
Open AccessSystolic array architectures have recently emerged as successful accelerators for deep convolutional neural network (CNN) inference. Such architectures can be used to efficiently execute general matrix–matrix multiplications ... -
An evaluation of energy vs accuracy tradeoffs for object detection accelerators
Caro Roca, Martí (Universitat Politècnica de Catalunya, 2022-07-01)
Master thesis
Restricted access - author's decision -
Efficient diverse redundant DNNs for autonomous driving
Caro Roca, Martí; Fornt Mas, Jordi; Abella Ferrer, Jaume (Institute of Electrical and Electronics Engineers (IEEE), 2023)
Conference report
Open AccessAutomotive applications with safety requirements must adhere to specific regulations such as ISO 26262, which imposes the use of diverse redundancy for the highest integrity levels (i.e., ASIL D). While this has been often ... -
Energy efficient object detection for automotive applications with YOLOv3 and approximate hardware
Fornt Mas, Jordi; Fontova Muste, Pau; Caro Roca, Martí; Abella Ferrer, Jaume; Moll Echeto, Francisco de Borja; Altet Sanahujes, Josep; Rubio Sola, Jose Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2023)
Conference report
Open AccessDeep neural networks are the dominant models for perception tasks in the automotive domain, but their high computational complexity makes it difficult to execute them in real time with an acceptable power consumption on ... -
Energy-efficient object detection: impact of weight clustering for different arithmetic representations
Caro Roca, Martí; Abella Ferrer, Jaume (Springer, 2024)
Article
Restricted access - publisher's policyObject detection in video streams is often realized with Deep Neural Networks (DNNs), which require fetching, to the computing unit where they are executed, large volumes of weights to process each image of the video. In ... -
Unitats funcionals aproximades per a processadors de baix consum
Caro Roca, Martí (Universitat Politécnica de Catalunya, 2020-01)
Bachelor thesis
Open AccessActualment els multiplicadors són una de les unitats funcionals que requereixen més consum d'energia degut al gran nombre de portes lògiques que contenen. Aprofitant el fet que diverses aplicacions poden tolerar un cert ...