Search Results - The Institute of Electrical and Electronics Engineers, Inc. (IEEE)

The Impact of Driving Styles on Fuel Consumption: A Data-Warehouse-and-Data-Mining-Based Discovery Process by Ferreira, Joao C., de Almeida, Jose, Rodrigues da Silva, Alberto

“…This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation…”
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A Survey on Vision Transformer by Han, Kai, Wang, Yunhe, Chen, Hanting, Chen, Xinghao, Guo, Jianyuan, Liu, Zhenhua, Tang, Yehui, Xiao, An, Xu, Chunjing, Xu, Yixing, Yang, Zhaohui, Zhang, Yiman, Tao, Dacheng

“…Transformer, first applied to the field of natural language processing, is a type of deep neural network mainly based on the self-attention mechanism. Thanks…”
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Image Segmentation Using Deep Learning: A Survey by Minaee, Shervin, Boykov, Yuri, Porikli, Fatih, Plaza, Antonio, Kehtarnavaz, Nasser, Terzopoulos, Demetri

“…Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis,…”
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Meta-Learning in Neural Networks: A Survey by Hospedales, Timothy, Antoniou, Antreas, Micaelli, Paul, Storkey, Amos

“…The field of meta-learning, or learning-to-learn, has seen a dramatic rise in interest in recent years. Contrary to conventional approaches to AI where tasks…”
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Event-Based Vision: A Survey by Gallego, Guillermo, Delbruck, Tobi, Orchard, Garrick, Bartolozzi, Chiara, Taba, Brian, Censi, Andrea, Leutenegger, Stefan, Davison, Andrew J., Conradt, Jorg, Daniilidis, Kostas, Scaramuzza, Davide

“…Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure…”
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A Survey on Knowledge Graphs: Representation, Acquisition, and Applications by Ji, Shaoxiong, Pan, Shirui, Cambria, Erik, Marttinen, Pekka, Yu, Philip S.

“…Human knowledge provides a formal understanding of the world. Knowledge graphs that represent structural relations between entities have become an increasingly…”
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Object Detection in 20 Years: A Survey by Zou, Zhengxia, Chen, Keyan, Shi, Zhenwei, Guo, Yuhong, Ye, Jieping

“…Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Over the past two…”
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A Comprehensive Survey on Transfer Learning by Zhuang, Fuzhen, Qi, Zhiyuan, Duan, Keyu, Xi, Dongbo, Zhu, Yongchun, Zhu, Hengshu, Xiong, Hui, He, Qing

“…Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related…”
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OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields by Cao, Zhe, Hidalgo, Gines, Simon, Tomas, Wei, Shih-En, Sheikh, Yaser

“…Realtime multi-person 2D pose estimation is a key component in enabling machines to have an understanding of people in images and videos. In this work, we…”
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U2Fusion: A Unified Unsupervised Image Fusion Network by Xu, Han, Ma, Jiayi, Jiang, Junjun, Guo, Xiaojie, Ling, Haibin

“…This study proposes a novel unified and unsupervised end-to-end image fusion network, termed as U2Fusion , which is capable of solving different fusion…”
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Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey by Jing, Longlong, Tian, Yingli

“…Large-scale labeled data are generally required to train deep neural networks in order to obtain better performance in visual feature learning from images or…”
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Squeeze-and-Excitation Networks by Hu, Jie, Shen, Li, Albanie, Samuel, Sun, Gang, Wu, Enhua

“…The central building block of convolutional neural networks (CNNs) is the convolution operator, which enables networks to construct informative features by…”
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Learning From Noisy Labels With Deep Neural Networks: A Survey by Song, Hwanjun, Kim, Minseok, Park, Dongmin, Shin, Yooju, Lee, Jae-Gil

“…Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. However, the quality of data labels is a concern…”
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A Survey on Multi-Task Learning by Zhang, Yu, Yang, Qiang

“…Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to leverage useful information contained in multiple related tasks to help…”
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Mask R-CNN by He, Kaiming, Gkioxari, Georgia, Dollar, Piotr, Girshick, Ross

“…We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while…”
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Plug-and-Play Image Restoration With Deep Denoiser Prior by Zhang, Kai, Li, Yawei, Zuo, Wangmeng, Zhang, Lei, Van Gool, Luc, Timofte, Radu

“…Recent works on plug-and-play image restoration have shown that a denoiser can implicitly serve as the image prior for model-based methods to solve many…”
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Deep Audio-Visual Speech Recognition by Afouras, Triantafyllos, Chung, Joon Son, Senior, Andrew, Vinyals, Oriol, Zisserman, Andrew

“…The goal of this work is to recognise phrases and sentences being spoken by a talking face, with or without the audio. Unlike previous works that have focussed…”
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6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities by Tataria, Harsh, Shafi, Mansoor, Molisch, Andreas F., Dohler, Mischa, Sjoland, Henrik, Tufvesson, Fredrik

“…Mobile communications have been undergoing a generational change every ten years or so. However, the time difference between the so-called "G's" is also…”
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Focal Loss for Dense Object Detection by Lin, Tsung-Yi, Goyal, Priya, Girshick, Ross, He, Kaiming, Dollar, Piotr

“…The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of…”
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Toward Causal Representation Learning by Scholkopf, Bernhard, Locatello, Francesco, Bauer, Stefan, Ke, Nan Rosemary, Kalchbrenner, Nal, Goyal, Anirudh, Bengio, Yoshua

“…The two fields of machine learning and graphical causality arose and are developed separately. However, there is, now, cross-pollination and increasing…”
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