Ara es mostren els items 17-36 de 36

    • 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)
      Text en actes de congrés
      Accés obert
      Deep 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 ...
    • Enhancing drones for law enforcement and capacity monitoring at open large events 

      Royo Chic, Pablo; Asenjo Carvajal, Àlex; Trujillo Gómez, Juan Manuel; Çetin, Ender; Barrado Muxí, Cristina (Multidisciplinary Digital Publishing Institute (MDPI), 2022-11-17)
      Article
      Accés obert
      Police tasks related with law enforcement and citizen protection have gained a very useful asset in drones. Crowded demonstrations, large sporting events, or summer festivals are typical situations when aerial surveillance ...
    • Enhancing low-level features with mid-level cues 

      Trulls Fortuny, Eduard (Universitat Politècnica de Catalunya, 2015-02-20)
      Tesi
      Accés obert
      Local features have become an essential tool in visual recognition. Much of the progress in computer vision over the past decade has built on simple, local representations such as SIFT or HOG. SIFT in particular shifted ...
    • Hierarchical object detection with deep reinforcement learning 

      Bellver, Míriam; Giró Nieto, Xavier; Marqués Acosta, Fernando; Torres Viñals, Jordi (IOS Press, 2017-11-23)
      Capítol de llibre
      Accés restringit per política de l'editorial
      Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, ...
    • Identificación de personas sin mascarilla en cámaras de seguridad 

      Adan Domínguez, Jordi (Universitat Politècnica de Catalunya, 2021-04-27)
      Projecte Final de Màster Oficial
      Accés restringit per decisió de l'autor
      Realitzat a/amb:   Makenai
      Hoy en día, la detección de objetos está presente en muchos aspectos de nuestra vida. Desde aplicaciones relacionadas con la seguridad hasta herramientas de entretenimiento, la detección de objetos juega un papel clave en ...
    • Image recognition in smart cities using neuronal networks 

      Hernandez Plaza, Eva (Universitat Politècnica de Catalunya, 2023-02-08)
      Treball Final de Grau
      Accés restringit per decisió de l'autor
      L'objectiu principal és desenvolupar un servei de detecció d'incidències en l'entorn urbà que es troben en mal estat on els ciutadans puguin denunciar-ho penjant una fotografia del lloc on es troba. La fotografia serà ...
    • Improving object detection in paintings based on time contexts 

      Marinescu, Maria Cristina; Reshetnikov, Artem; More López, Joaquim (Institute of Electrical and Electronics Engineers (IEEE), 2020)
      Text en actes de congrés
      Accés obert
      This paper proposes a novel approach to object detection for the Cultural Heritage domain, which relies on combining Deep Learning and semantic metadata about candidate objects extracted from existing sources such as ...
    • Intelligent weed management based on object detection neural networks in tomato crops 

      López Correa, Juan Manuel; Moreno Párrizas, Hugo; Ribeiro Seijas, Angela; Andujar Sánchez, Dionisio (Multidisciplinary Digital Publishing Institute (MDPI), 2022-11-24)
      Article
      Accés obert
      As the tomato (Solanum lycopersicum L.) is one of the most important crops worldwide, and the conventional approach for weed control compromises its potential productivity. Thus, the automatic detection of the most aggressive ...
    • IntPred: flexible, fast, and accurate object detection for autonomous driving systems 

      Tabani, Hamid; Fusi, Matteo; Kosmidis, Leonidas; Abella Ferrer, Jaume; Cazorla Almeida, Francisco Javier (Association for Computing Machinery (ACM), 2020)
      Text en actes de congrés
      Accés obert
      Deep Neural-Network (DNN) based Object Detection is one of the most important and time-consuming stages of Autonomous Driving software in cars. In non-critical domains, the performance and energy requirements of object ...
    • Machine learning on deep neural networks and object tracking applied to motion of airplanes 

      Martin Torres, Claudia (Universitat Politècnica de Catalunya, 2020-09-14)
      Treball Final de Grau
      Accés obert
      The aim of this project is to understand the concepts underlying machine learning and how to implement those. To achieve this purpose, an exhaustive study of the origins of this technology has been made, describing the ...
    • Measures and meta-measures for the supervised evaluation of image segmentation 

      Pont Tuset, Jordi; Marqués Acosta, Fernando (IEEE Computer Society Publications, 2013)
      Text en actes de congrés
      Accés obert
      This paper tackles the supervised evaluation of image segmentation algorithms. First, it surveys and structures the measures used to compare the segmentation results with a ground truth database, and proposes a new measure: ...
    • Multi-task Deep Learning models for real-time deployment in embedded systems 

      Martí I Rabadán, Miquel (Universitat Politècnica de Catalunya, 2017-05-23)
      Projecte Final de Màster Oficial
      Accés obert
      Realitzat a/amb:   Kungl. tekniska högskolan. Skolan för elektroteknik och datavetenskap
      Multitask Learning (MTL) was conceived as an approach to improve the generalization ability of machine learning models. When applied to neural networks, multitask models take advantage of sharing resources for reducing the ...
    • Object recognition in urban hyperspectral images using binary partition tree representation 

      Valero, Silvia; Salembier Clairon, Philippe Jean; Chanussot, Jocelyn (Institute of Electrical and Electronics Engineers (IEEE), 2012)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      In this work, an image representation based on Binary Partition Tree is proposed for object detection in hyperspectral images. The BPT representation defines a search space for constructing a robust object identification ...
    • Pedestrian detection and tracking in urban mobility from different perspectives 

      Elbaz Trojman, Míriam (Universitat Politècnica de Catalunya, 2023-05-25)
      Treball Final de Grau
      Accés obert
      This thesis is about exploring the possibility to make a system that could be implemented in e-scooters to help their users to use them in a secure manner. The objective of this thesis is to find if it is possible to train ...
    • Real-time logo detection in brand-related social media images 

      Orti, Oscar; Tous Liesa, Rubén; Gómez Parada, Mauro; Poveda, Jonatan; Cruz de la Cruz, Stalin Leonel; Wust, Otto (Springer, 2019)
      Text en actes de congrés
      Accés obert
      This paper presents a work consisting in using deep convolutional neural networks (CNNs) for real-time logo detection in brand-related social media images. The final goal is to facilitate searching and discovering ...
    • Region-based face detection, segmentation and tracking. framework definition and application to other objects 

      Vilaplana Besler, Verónica (Universitat Politècnica de Catalunya, 2010-12-17)
      Tesi
      Accés obert
      One of the central problems in computer vision is the automatic recognition of object classes. In particular, the detection of the class of human faces is a problem that generates special interest due to the large number ...
    • Robust and real-time detection and tracking of moving objects with minimum 2d LiDAR information to advance autonomous cargo handling in ports 

      Vaquero Gómez, Víctor; Repiso Polo, Ely; Sanfeliu Cortés, Alberto (Multidisciplinary Digital Publishing Institute (MDPI), 2018-12-29)
      Article
      Accés obert
      Detecting and tracking moving objects (DATMO) is an essential component for autonomous driving and transportation. In this paper, we present a computationally low-cost and robust DATMO system which uses as input only 2D ...
    • Unidimensional multiscale local features for object detection under rotation and mild occlusions 

      Villamizar Vergel, Michael Alejandro; Sanfeliu Cortés, Alberto; Andrade-Cetto, Juan (Springer, 2007)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows ...
    • Work-efficient parallel non-maximum suppression kernels 

      Oro García, David; Fernandez Tena, Carles; Martorell Bofill, Xavier; Hernando Pericás, Francisco Javier (Wiley Heyden, 2020-08-21)
      Article
      Accés obert
      In the context of object detection, sliding-window classifiers and single-shot convolutional neural network (CNN) meta-architectures typically yield multiple overlapping candidate windows with similar high scores around ...
    • Worst case execution time and power estimation of multicore and GPU software: a pedestrian detection use case 

      Rodríguez Ferrández, Iván; Jover Álvarez, Álvaro; Trompouki, Matina Maria; Kosmidis, Leonidas; Cazorla Almeida, Francisco Javier (Association for Computing Machinery (ACM), 2023)
      Comunicació de congrés
      Accés obert
      Worst Case Execution Time estimation of software running on parallel platforms is a challenging task, due to resource interference of other tasks and the complexity of the underlying CPU and GPU hardware architectures. ...